{ "schema": "5lc-selection-review/1", "sublayer": "data-platforms", "asOf": "2026-10-21", "status": "reviewed_representative_set_with_unresolved_cutoff", "scope": "Commercial data, analytics and observability platforms used to build and operate AI applications. Infrastructure cloud revenue, foundation-model revenue, financing and benchmark capability are not selection measures.", "eligibility": "Current sold service or delivered deployment; open-source community use alone is not commercial customer count. Public and private suppliers receive the same role test. Business units are consolidated to their economic company group.", "predefinedFunctions": [ { "id": "lakehouse-analytics", "description": "Analytical warehouses and lakehouses that store, govern and process application data.", "required": true }, { "id": "operational-retrieval", "description": "Operational databases, vector retrieval and search supplying application context.", "required": true }, { "id": "data-movement", "description": "Data ingestion, streaming and transformation connecting operational sources to AI applications.", "required": true }, { "id": "operational-ai-context", "description": "Governed context and operational application layers connecting models to business decisions.", "required": true }, { "id": "observability", "description": "Monitoring, tracing and evaluation of deployed applications and agents.", "required": true } ], "universe": { "initialFile": "candidate-universe.json", "reconciledCandidates": [ { "entityId": "microsoft", "name": "Microsoft", "economicParent": "microsoft", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement", "operational-ai-context" ], "sourceIds": [ "ms:fabric" ], "roleEvidence": "Fabric has more than 40,000 paid customers. Azure or Microsoft revenue is not attributed to Fabric." }, { "entityId": "amazon", "name": "Amazon", "economicParent": "amazon", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement", "operational-retrieval" ], "sourceIds": [ "aws:redshift" ], "roleEvidence": "Redshift and integrated operational sources provide a current commercial data platform; AWS revenue is not data-platform revenue." }, { "entityId": "alphabet", "name": "Alphabet", "economicParent": "alphabet", "eligible": true, "functions": [ "lakehouse-analytics", "operational-ai-context" ], "sourceIds": [ "google:bigquery" ], "roleEvidence": "BigQuery is a current managed analytical platform. Its historical tens-of-thousands organization claim has no exact current paying denominator." }, { "entityId": "oracle", "name": "Oracle", "economicParent": "oracle", "eligible": true, "functions": [ "lakehouse-analytics", "operational-retrieval", "operational-ai-context" ], "sourceIds": [ "oracle:q1" ], "roleEvidence": "Current AI Data Platform and database business; the latest results do not isolate comparable AI-data revenue." }, { "entityId": "ibm", "name": "IBM", "economicParent": "ibm", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement", "operational-retrieval", "operational-ai-context" ], "sourceIds": [ "ibm:ibm-ar25", "ibm:cflt-close" ], "roleEvidence": "Reported Data business plus completed Confluent and DataStax consolidation. Data revenue is broader than generative AI." }, { "entityId": "databricks", "name": "Databricks", "economicParent": "databricks", "eligible": true, "functions": [ "lakehouse-analytics", "operational-retrieval", "operational-ai-context" ], "sourceIds": [ "databricks:dbx-pr-aug2026" ], "roleEvidence": "Large disclosed current platform run rate, separately disclosed warehouse and Lakebase activity. Neon is consolidated." }, { "entityId": "snowflake", "name": "Snowflake", "economicParent": "snowflake", "eligible": true, "functions": [ "lakehouse-analytics", "operational-ai-context" ], "sourceIds": [ "snowflake:snow-q2-current" ], "roleEvidence": "Recognized platform revenue and active AI accounts; accounts and paid AI customers are not equivalent." }, { "entityId": "mongodb", "name": "MongoDB", "economicParent": "mongodb", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "mongodb:mdb-q2-current", "mongodb:mdb-2026-report" ], "roleEvidence": "Operational Atlas database and Voyage retrieval capabilities; parent revenue includes non-AI database work." }, { "entityId": "palantir", "name": "Palantir", "economicParent": "palantir", "eligible": true, "functions": [ "operational-ai-context" ], "sourceIds": [ "palantir:pltr-q2-issuer", "palantir:pltr-q2-slides" ], "roleEvidence": "Material recognized commercial and government platform activity and defined revenue-generating customer count." }, { "entityId": "fivetran", "name": "Fivetran / dbt Labs", "economicParent": "fivetran", "eligible": true, "functions": [ "data-movement" ], "sourceIds": [ "fivetran:ft-merger-close", "fivetran:ft-census" ], "roleEvidence": "Independent ingestion and transformation layer. Merger completed; anticipated combined ARR is not realized revenue." }, { "entityId": "datadog", "name": "Datadog", "economicParent": "datadog", "eligible": true, "functions": [ "observability" ], "sourceIds": [ "datadog:dd-q2-current" ], "roleEvidence": "Recognized observability revenue, large-spend customers and current agent monitoring; AI-only revenue unavailable." }, { "entityId": "dynatrace", "name": "Dynatrace", "economicParent": "dynatrace", "eligible": true, "functions": [ "observability" ], "sourceIds": [ "dynatrace:dt-q1-filing", "dynatrace:dt-arize-current" ], "roleEvidence": "Recognized monitoring revenue and completed Arize evaluation acquisition; ARR is distinct from annualized log consumption." }, { "entityId": "elastic", "name": "Elastic", "economicParent": "elastic", "eligible": true, "functions": [ "operational-retrieval", "observability" ], "sourceIds": [ "elastic:estc-q1-current" ], "roleEvidence": "Search, retrieval, security and observability revenue; Cloud and sales-led categories overlap." }, { "entityId": "grafana-labs", "name": "Grafana Labs", "economicParent": "grafana-labs", "eligible": true, "functions": [ "observability" ], "sourceIds": [ "grafana-labs:gl-pr-2026-08" ], "roleEvidence": "Material ARR and deployed open/commercial observability; free-plus-paid Assistant organizations are not paid customers." }, { "entityId": "supabase", "name": "Supabase", "economicParent": "supabase", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "supabase:s-turso" ], "roleEvidence": "Commercial managed Postgres backend and substantial developer/database creation activity; no comparable current revenue disclosed." }, { "entityId": "sap", "name": "SAP / Dremio / Reltio", "economicParent": "sap", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement", "operational-ai-context" ], "sourceIds": [ "sap:sap-h1-otc", "sap:sap-dremio-close", "sap:sap-autonomous-enterprise", "dremio:shell" ], "roleEvidence": "SAP Business Data Cloud combines enterprise context, analytics and acquired Dremio lakehouse and Reltio master-data capabilities. Dremio closed July 6 and Reltio May 7; neither is an independent economic group. SAP company revenue is not data-platform revenue." }, { "entityId": "clickhouse", "name": "ClickHouse", "economicParent": "clickhouse", "eligible": true, "functions": [ "lakehouse-analytics", "observability" ], "sourceIds": [ "clickhouse:may" ], "roleEvidence": "Company growth paragraph: annual run-rate revenue, Cloud customers; Langfuse acquisition and product status; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "starburst", "name": "Starburst", "economicParent": "starburst", "eligible": true, "functions": [ "lakehouse-analytics", "operational-ai-context" ], "sourceIds": [ "starburst:arr" ], "roleEvidence": "Crossed $100M ARR last year; $20M AI annual run rate; financial-services percentages conflict and are excluded; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "pinecone", "name": "Pinecone", "economicParent": "pinecone", "eligible": true, "functions": [ "operational-retrieval", "operational-ai-context" ], "sourceIds": [ "pinecone:nexus" ], "roleEvidence": "GA paragraph and About: over 10,000 customers and 1M developers; not defined as paying; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "redis", "name": "Redis", "economicParent": "redis", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "redis:aws" ], "roleEvidence": "Redis Cloud marketplace, vector search, semantic caching and agent memory; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "weaviate", "name": "Weaviate", "economicParent": "weaviate", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "weaviate:docsbot" ], "roleEvidence": "Managed Cloud deployment; DocsBot user/question counts are not Weaviate commercial scale; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "airbyte", "name": "Airbyte", "economicParent": "airbyte", "eligible": true, "functions": [ "data-movement" ], "sourceIds": [ "airbyte:pricing" ], "roleEvidence": "Paid standard, plus and enterprise plans; free/Core adoption not counted as paying customers; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "new-relic", "name": "New Relic", "economicParent": "new-relic", "eligible": true, "functions": [ "observability" ], "sourceIds": [ "newrelic:agent" ], "roleEvidence": "Intelligent Workloads, Agentic AI Monitoring, Lens and Notebooks announcement; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "cisco", "name": "Cisco / Splunk", "economicParent": "cisco", "eligible": true, "functions": [ "observability" ], "sourceIds": [ "cisco:splunk" ], "roleEvidence": "Observability Cloud, AppDynamics and ITSI; AI application observability and Progressive Insurance case; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "alibaba", "name": "Alibaba", "economicParent": "alibaba", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement" ], "sourceIds": [ "alibaba:hologres" ], "roleEvidence": "Commercial managed analytical database; MaxCompute/Flink/DataWorks integration; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "huawei", "name": "Huawei", "economicParent": "huawei", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "huawei:gaussdb" ], "roleEvidence": "Distributed relational database description; current aggregate revenue/adoption not provided; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "tencent", "name": "Tencent", "economicParent": "tencent", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "tencent:vdb" ], "roleEvidence": "Managed vector retrieval for language-model knowledge and recommendations; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "teradata", "name": "Teradata", "economicParent": "teradata", "eligible": true, "functions": [ "lakehouse-analytics", "operational-ai-context" ], "sourceIds": [ "teradata:q2" ], "roleEvidence": "Issuer release: revenue table, ARR definitions and Autonomous Knowledge Platform; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "cloudera", "name": "Cloudera", "economicParent": "cloudera", "eligible": true, "functions": [ "lakehouse-analytics", "data-movement" ], "sourceIds": [ "cloudera:customers" ], "roleEvidence": "Named Continental, BT, SAIC-Volkswagen and Amdocs deployment descriptions; lakehouse/streaming platform; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "qdrant", "name": "Qdrant", "economicParent": "qdrant", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "qdrant:cloud" ], "roleEvidence": "Managed service and production case descriptions; serverless remains coming soon; current comparable relevant revenue is unknown unless listed separately below." }, { "entityId": "zilliz", "name": "Zilliz", "economicParent": "zilliz", "eligible": true, "functions": [ "operational-retrieval" ], "sourceIds": [ "zilliz:may" ], "roleEvidence": "Existing BYOC clusters and paid usage-based Cloud; Vector Lakebase public preview separately identified; current comparable relevant revenue is unknown unless listed separately below." } ], "changes": [ "Expanded beyond prior roster to all major cloud data providers, independent lakehouse/query vendors, established analytical platforms, vector specialists and observability peers.", "Dremio and Reltio consolidated into SAP after completed acquisitions.", "DataStax and Confluent consolidated into IBM; dbt Labs into Fivetran; Neon into Databricks; Arize into Dynatrace; Langfuse into ClickHouse; Splunk into Cisco; Huawei Cloud into Huawei." ], "aliases": [ { "unit": "datastax", "parent": "ibm" }, { "unit": "confluent", "parent": "ibm" }, { "unit": "dbt-labs", "parent": "fivetran" }, { "unit": "neon", "parent": "databricks" }, { "unit": "arize", "parent": "dynatrace" }, { "unit": "langfuse", "parent": "clickhouse" }, { "unit": "splunk", "parent": "cisco" }, { "unit": "huawei-cloud", "parent": "huawei" }, { "unit": "dremio", "parent": "sap" }, { "unit": "reltio", "parent": "sap" } ] }, "parameters": { "maxCompanies": 10, "score": null, "weights": null, "normalization": null, "coverageTarget": null, "marketDenominator": null, "reason": "A defensible global relevant-activity denominator is unavailable. Revenue, ARR, consumption, active accounts and developers have different definitions. Numeric weights would conceal rather than solve that problem. Selection uses explicit role coverage and disclosed activity, with competing ten-company sets." }, "rawObservations": [ { "entityId": "ibm", "measure": "Data revenue (Software sub-line)", "value": "6,299", "operator": "=", "unit": "USD millions", "economicPeriod": "FY2025 (year ended 2025-12-31)", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "ibm:ibm-ar25" ], "evidence": "filing", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "databricks", "measure": "Revenue run-rate", "value": ">7B", "operator": "=", "unit": "USD (annualised)", "economicPeriod": "Quarter called Q2 in August 13, 2026 release; fiscal dates not specified", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "databricks:dbx-pr-aug2026" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "databricks", "measure": "Lakehouse (data warehousing) revenue run-rate", "value": ">1.5B", "operator": "=", "unit": "USD (annualised)", "economicPeriod": "Quarter called Q2 in August 13, 2026 release; fiscal dates not specified", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "databricks:dbx-pr-aug2026" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "databricks", "measure": "Lakebase revenue run-rate", "value": ">100M", "operator": "=", "unit": "USD (annualised)", "economicPeriod": "Quarter called Q2 in August 13, 2026 release; fiscal dates not specified", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "databricks:dbx-pr-aug2026" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "snowflake", "measure": "Total quarterly revenue", "value": "1546.793", "operator": "=", "unit": "USD millions", "economicPeriod": "Q2 FY2027, ended July 31, 2026", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "snowflake:snow-q2-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "snowflake", "measure": "CoCo active accounts", "value": ">9100", "operator": "=", "unit": "accounts", "economicPeriod": "Average weekly active accounts during final four weeks of Q2 FY2027", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "snowflake:snow-q2-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "snowflake", "measure": "CoWork active accounts", "value": ">5800", "operator": "=", "unit": "accounts", "economicPeriod": "Average weekly active accounts during final four weeks of Q2 FY2027", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "snowflake:snow-q2-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "mongodb", "measure": "Quarterly revenue", "value": "771.8", "operator": "=", "unit": "USD millions", "economicPeriod": "Q2 FY2027 (quarter ended 2026-07-31), up 30% year on year", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "mongodb:mdb-q2-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "palantir", "measure": "Quarterly revenue", "value": "1935.464", "operator": "=", "unit": "USD millions", "economicPeriod": "Q2 2026 (quarter)", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "palantir:pltr-q2-issuer" ], "evidence": "filing", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "palantir", "measure": "Customers", "value": "1049 total; 870 commercial; 653 U.S. commercial", "operator": "=", "unit": "organizations generating revenue in the trailing year", "economicPeriod": "TTM ended June 30, 2026", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "palantir:pltr-q2-slides" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "fivetran", "measure": "Fivetran standalone ARR", "value": "more than 300", "operator": "=", "unit": "USD millions", "economicPeriod": "May 2025 (pre-merger)", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "fivetran:ft-census" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "datadog", "measure": "Quarterly revenue", "value": "1.12", "operator": "=", "unit": "USD billions", "economicPeriod": "Q2 2026 (quarter ended 2026-06-30), up 36% year on year", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "datadog:dd-q2-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "dynatrace", "measure": "Quarterly revenue", "value": "554.548", "operator": "=", "unit": "USD millions", "economicPeriod": "Q1 FY2027 (quarter ended 2026-06-30), up 16% (15% constant currency)", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "dynatrace:dt-q1", "dynatrace:dt-q1-filing" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "dynatrace", "measure": "Annual recurring revenue", "value": "2135.982", "operator": "=", "unit": "USD millions", "economicPeriod": "Q1 FY2027, up 17% year on year", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "dynatrace:dt-q1", "dynatrace:dt-q1-filing" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "elastic", "measure": "Quarterly revenue", "value": "478.113", "operator": "=", "unit": "USD millions", "economicPeriod": "Q1 FY2027 ended July 31, 2026", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "elastic:estc-q1-current" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "grafana-labs", "measure": "Annual recurring revenue", "value": "more than 600", "operator": "=", "unit": "USD millions", "economicPeriod": "ARR as of August 2026", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "grafana-labs:gl-pr-2026-08" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "grafana-labs", "measure": "Customers", "value": "10,000+", "operator": "=", "unit": "customers; company definition not specified", "economicPeriod": "August 2026 (7,000+ in September 2025)", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "grafana-labs:gl-pr-2026-08", "grafana-labs:gl-pr-2025-09" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "supabase", "measure": "Developers building on Supabase", "value": "Nearly 10 million", "operator": "=", "unit": "developers", "economicPeriod": "As of the Series F", "boundary": "Company definition retained; neither an AI-only measure nor a market-share denominator. Subsets and different periods must not be added.", "sourceIds": [ "supabase:s-series-f-current", "supabase:s-tc" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "microsoft", "measure": "Paid Fabric customers", "value": 40000, "operator": ">", "unit": "customers", "economicPeriod": "FY2026 Q4", "boundary": "Current paying organizations, not seats. Foundry overlap is a subset.", "sourceIds": [ "ms:fabric" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "microsoft", "measure": "Customers using both Foundry and Fabric", "value": 17000, "operator": ">", "unit": "customers", "economicPeriod": "FY2026 Q4", "boundary": "Overlaps Fabric total; never added to the total.", "sourceIds": [ "ms:fabric" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "clickhouse", "measure": "Annual run-rate revenue", "value": 250, "operator": ">", "unit": "USD millions", "economicPeriod": "May 27 2026", "boundary": "Headline uses ARR; body says annual run-rate revenue. Not recognized annual revenue.", "sourceIds": [ "clickhouse:may" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "clickhouse", "measure": "Cloud customers", "value": 4000, "operator": "=", "unit": "customers", "economicPeriod": "May 27 2026", "boundary": "Cloud customer definition; paying criterion not specified in announcement.", "sourceIds": [ "clickhouse:may" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "starburst", "measure": "Annual recurring revenue", "value": 100, "operator": ">", "unit": "USD millions", "economicPeriod": "Threshold crossed during 2025; disclosed Feb 18 2026", "boundary": "Historical milestone, not current October ARR.", "sourceIds": [ "starburst:arr" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "starburst", "measure": "AI annual run rate", "value": 20, "operator": "=", "unit": "USD millions", "economicPeriod": "Feb 18 2026 announcement", "boundary": "AI product annualized rate; scope/accounting not independently audited.", "sourceIds": [ "starburst:arr" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "pinecone", "measure": "Customers", "value": 10000, "operator": ">", "unit": "customers", "economicPeriod": "Aug 6 2026", "boundary": "Paying criterion undefined; developer count is separate and overlapping.", "sourceIds": [ "pinecone:nexus" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "teradata", "measure": "Quarterly total revenue", "value": 410, "operator": "=", "unit": "USD millions", "economicPeriod": "Q2 ended June 30 2026", "boundary": "363 recurring + 8 perpetual/software/hardware/other + 39 consulting; not AI-only.", "sourceIds": [ "teradata:q2" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "teradata", "measure": "Total ARR", "value": 1509, "operator": "=", "unit": "USD millions", "economicPeriod": "June 30 2026", "boundary": "Annual value of binding term contracts including cloud, AI services, software, hardware rental, maintenance and upgrades.", "sourceIds": [ "teradata:q2" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "teradata", "measure": "Public cloud ARR", "value": 686, "operator": "=", "unit": "USD millions", "economicPeriod": "June 30 2026", "boundary": "Subset of total ARR; not additive.", "sourceIds": [ "teradata:q2" ], "evidence": "company_stated", "inputType": "measured", "comparisonUse": "role_specific_only" }, { "entityId": "amazon", "measure": "Comparable current relevant activity", "value": null, "operator": "=", "unit": "unavailable", "economicPeriod": "Current review", "boundary": "Not disclosed on comparable product boundary in inspected evidence; never replaced by parent revenue, funding or zero.", "sourceIds": [ "aws:redshift" ], "evidence": "company_stated", "inputType": "missing", "comparisonUse": "role_specific_only" }, { "entityId": "alphabet", "measure": "Comparable current relevant activity", "value": null, "operator": "=", "unit": "unavailable", "economicPeriod": "Current review", "boundary": "Not disclosed on comparable product boundary in inspected evidence; never replaced by parent revenue, funding or zero.", "sourceIds": [ "google:bigquery" ], "evidence": "company_stated", "inputType": "missing", "comparisonUse": "role_specific_only" }, { "entityId": "oracle", "measure": "Comparable current relevant activity", "value": null, "operator": "=", "unit": "unavailable", "economicPeriod": "Current review", "boundary": "Not disclosed on comparable product boundary in inspected evidence; never replaced by parent revenue, funding or zero.", "sourceIds": [ "oracle:q1" ], "evidence": "company_stated", "inputType": "missing", "comparisonUse": "role_specific_only" }, { "entityId": "redis", "measure": "Comparable current relevant activity", "value": null, "operator": "=", "unit": "unavailable", "economicPeriod": "Current review", "boundary": "Not disclosed on comparable product boundary in inspected evidence; never replaced by parent revenue, funding or zero.", "sourceIds": [ "redis:aws" ], "evidence": "company_stated", "inputType": "missing", "comparisonUse": "role_specific_only" }, { "entityId": "weaviate", "measure": "Comparable current relevant activity", "value": null, "operator": "=", "unit": "unavailable", "economicPeriod": "Current review", "boundary": "Not disclosed on comparable product boundary in inspected evidence; never replaced by parent revenue, funding or zero.", "sourceIds": [ "weaviate:docsbot" ], "evidence": "company_stated", "inputType": "missing", "comparisonUse": "role_specific_only" }, { "entityId": "airbyte", "measure": "Comparable current relevant activity", 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description; current aggregate revenue/adoption not provided", "type": "company" }, "tencent:vdb": { "url": "https://www.tencentcloud.com/products/vdb", "title": "Tencent Cloud — VectorDB", "publisher": "Tencent Cloud", "publishedDate": null, "accessedDate": "2026-10-21", "locator": "Managed vector retrieval for language-model knowledge and recommendations", "type": "company" }, "teradata:q2": { "url": "https://www.prnewswire.com/news-releases/teradata-reports-second-quarter-2026-financial-results-302842929.html", "title": "Teradata — Q2 results", "publisher": "Teradata", "publishedDate": "2026-08-04", "accessedDate": "2026-10-21", "locator": "Issuer release: revenue table, ARR definitions and Autonomous Knowledge Platform", "type": "company" }, "cloudera:customers": { "url": "https://www.cloudera.com/customers.html", "title": "Cloudera — customers and platform", "publisher": "Cloudera", "publishedDate": null, "accessedDate": "2026-10-21", "locator": "Named Continental, BT, SAIC-Volkswagen and Amdocs deployment descriptions; lakehouse/streaming platform", "type": "company" }, "qdrant:cloud": { "url": "https://qdrant.tech/cloud/", "title": "Qdrant — managed Cloud", "publisher": "Qdrant", "publishedDate": null, "accessedDate": "2026-10-21", "locator": "Managed service and production case descriptions; serverless remains coming soon", "type": "company" }, "zilliz:may": { "url": "https://docs.zilliz.com/docs/release-notes-2605", "title": "Zilliz — Cloud release notes", "publisher": "Zilliz", "publishedDate": "2026-05-13", "accessedDate": "2026-10-21", "locator": "Existing BYOC clusters and paid usage-based Cloud; Vector Lakebase public preview separately identified", "type": "company" } }, "calculations": [ { "name": "Same-quarter accounting baseline", "formula": "Sort reported USD revenue for quarter ended June 30 2026, descending; no normalization or extrapolation", "inputs": { "palantir": 1935.464, "datadog": 1120.0, "dynatrace": 554.548, "teradata": 410.0 }, "result": [ "palantir", "datadog", "dynatrace", "teradata" ], "unit": "USD millions", "sourceIds": [ "palantir:pltr-q2-issuer", "datadog:dd-q2-current", "dynatrace:dt-q1-filing", "teradata:q2" ], "interpretation": "Reproducible accounting ordering among four disclosed businesses only. Their functional mixes differ; this cannot establish global AI-data importance or rank missing peers." }, { "name": "One-month-offset accounting cohort", "formula": "Sort reported USD revenue for quarter ended July 31 2026, descending", "inputs": { "snowflake": 1546.793, "mongodb": 771.8, "elastic": 478.113 }, "result": [ "snowflake", "mongodb", "elastic" ], "unit": "USD millions", "sourceIds": [ "snowflake:snow-q2-current", "mongodb:mdb-q2-current", "elastic:estc-q1-current" ], "interpretation": "Separate period cohort; not mixed with June-ending companies or private ARR." }, { "name": "Teradata component reconciliation", "formula": "363 + 8 + 39", "value": 410, "unit": "USD millions", "sourceIds": [ "teradata:q2" ] }, { "name": "Teradata cloud share of its own ARR", "formula": "686 / 1509 * 100", "value": 45.46056991385023, "unit": "percent of Teradata ARR", "sourceIds": [ "teradata:q2" ], "interpretation": "Internal mix only, not global market share." }, { "name": "Selected function coverage", "formula": "For each declared function f, count selected economic groups with documented current role f", "value": { "lakehouse-analytics": 6, "operational-retrieval": 4, "data-movement": 4, "operational-ai-context": 6, "observability": 1 }, "unit": "economic groups", "interpretation": "Coverage of declared functions, not percentage of economic market." }, { "name": "Sensitivity overlap", "formula": "Jaccard(B,S) = |B intersection S| / |B union S|; retained = |B intersection S|", "interpretation": "Describes differences between disclosed editorial scenarios, not a statistical probability." } ], "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "datadog" ], "selectedReasons": { "microsoft": "Paid Fabric adoption and a broad integrated data/AI platform establish a distinct large commercial role.", "amazon": "Commercial Redshift data infrastructure links operational data, analytics and model services across AWS. Scale is qualified because product revenue is not disclosed.", "alphabet": "BigQuery represents Google Cloud analytical data and agent-context infrastructure; group revenue is excluded.", "ibm": "Data software plus Confluent streaming and DataStax retrieval provide substantial hybrid enterprise coverage. Current comparability remains imperfect.", "databricks": "Disclosed current platform, warehouse and operational-database activity support lakehouse and AI data representation.", "snowflake": "Large recognized warehouse/platform revenue and measured active AI accounts support current enterprise adoption.", "mongodb": "Represents operational application databases and retrieval, with separately disclosed Atlas activity.", "palantir": "Provides a distinct governed operational context layer across commercial and government AI applications.", "fivetran": "Preserves independent ingestion and transformation representation after dbt integration; unknown current combined ARR is not treated as zero.", "datadog": "Represents deployed-application observability with substantial recognized activity. Other observability vendors remain valid cutoff alternatives." }, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "datadog" ] }, "alternativeCutoffSets": [ { "name": "enterprise semantic context", "remove": [ "palantir" ], "add": [ "sap" ], "assumption": "Prioritize SAP Business Data Cloud, acquired Dremio and Reltio for enterprise data context. SAP group revenue is not used as a data-platform measure.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "fivetran", "datadog", "sap" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "sap" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran", "sap" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "sap" ], "observability": [ "datadog" ] } }, { "name": "database-incumbent emphasis", "remove": [ "ibm" ], "add": [ "oracle" ], "assumption": "Prioritize the database incumbent and current AI Data Platform over IBM hybrid/streaming coverage; missing Oracle product revenue is not a disqualification.", "selectedIds": [ "microsoft", "amazon", "alphabet", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "datadog", "oracle" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "databricks", "snowflake", "oracle" ], "operational-retrieval": [ "amazon", "databricks", "mongodb", "oracle" ], "data-movement": [ "microsoft", "amazon", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "databricks", "snowflake", "palantir", "oracle" ], "observability": [ "datadog" ] } }, { "name": "two database incumbents", "remove": [ "fivetran" ], "add": [ "oracle" ], "assumption": "Accept integrated cloud and IBM streaming coverage instead of a dedicated independent ingestion/transformation supplier.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "palantir", "datadog", "oracle" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "oracle" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb", "oracle" ], "data-movement": [ "microsoft", "amazon", "ibm" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir", "oracle" ], "observability": [ "datadog" ] } }, { "name": "search and retrieval emphasis", "remove": [ "mongodb" ], "add": [ "elastic" ], "assumption": "Search and retrieval plus monitoring receive priority over operational document-database representation.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "palantir", "fivetran", "datadog", "elastic" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "elastic" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "datadog", "elastic" ] } }, { "name": "evaluation and observability emphasis", "remove": [ "datadog" ], "add": [ "dynatrace" ], "assumption": "Completed Arize evaluation acquisition supports a different observability representative.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "dynatrace" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "dynatrace" ] } }, { "name": "open observability emphasis", "remove": [ "datadog" ], "add": [ "grafana-labs" ], "assumption": "Give greater emphasis to open/commercial observability without converting free users into paid customers.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "grafana-labs" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "grafana-labs" ] } }, { "name": "vector specialist emphasis", "remove": [ "mongodb" ], "add": [ "pinecone" ], "assumption": "A specialist knowledge/retrieval supplier substitutes for the broader operational database; missing revenue is retained.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "palantir", "fivetran", "datadog", "pinecone" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "pinecone" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir", "pinecone" ], "observability": [ "datadog" ] } }, { "name": "regional breadth", "remove": [ "alphabet" ], "add": [ "alibaba" ], "assumption": "Give greater emphasis to commercial Chinese cloud data products; no country quota or group-cloud revenue score is introduced.", "selectedIds": [ "microsoft", "amazon", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "datadog", "alibaba" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "ibm", "databricks", "snowflake", "alibaba" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran", "alibaba" ], "operational-ai-context": [ "microsoft", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "datadog" ] } }, { "name": "independent analytics challenge", "remove": [ "alphabet", "snowflake" ], "add": [ "clickhouse", "starburst" ], "assumption": "Increase independent analytical architecture coverage; lower or older disclosed run rates do not automatically make these suppliers irrelevant.", "selectedIds": [ "microsoft", "amazon", "ibm", "databricks", "mongodb", "palantir", "fivetran", "datadog", "clickhouse", "starburst" ], "retained": 8, "jaccard": 0.6666666666666666, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "ibm", "databricks", "clickhouse", "starburst" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "ibm", "databricks", "palantir", "starburst" ], "observability": [ "datadog", "clickhouse" ] } }, { "name": "private enterprise platform challenge", "remove": [ "alphabet" ], "add": [ "cloudera" ], "assumption": "Allow commercially established private hybrid data platforms with unreported current revenue to contest the cutoff.", "selectedIds": [ "microsoft", "amazon", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "datadog", "cloudera" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "ibm", "databricks", "snowflake", "cloudera" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran", "cloudera" ], "operational-ai-context": [ "microsoft", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "datadog" ] } }, { "name": "observability consolidation challenge", "remove": [ "datadog" ], "add": [ "cisco" ], "assumption": "Choose Splunk within its Cisco parent instead; do not count Splunk as an additional independent supplier.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake", "mongodb", "palantir", "fivetran", "cisco" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "snowflake" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "snowflake", "palantir" ], "observability": [ "cisco" ] } }, { "name": "long-established analytical warehouse", "remove": [ "snowflake" ], "add": [ "teradata" ], "assumption": "Emphasize hybrid installed-base representation using disclosed current revenue and ARR, without equating ARR to revenue.", "selectedIds": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "mongodb", "palantir", "fivetran", "datadog", "teradata" ], "retained": 9, "jaccard": 0.8181818181818182, "allFunctionsCovered": true, "functionCoverage": { "lakehouse-analytics": [ "microsoft", "amazon", "alphabet", "ibm", "databricks", "teradata" ], "operational-retrieval": [ "amazon", "ibm", "databricks", "mongodb" ], "data-movement": [ "microsoft", "amazon", "ibm", "fivetran" ], "operational-ai-context": [ "microsoft", "alphabet", "ibm", "databricks", "palantir", "teradata" ], "observability": [ "datadog" ] } } ], "sensitivity": { "stableWithinDeclaredScenarios": [ "amazon", "databricks", "microsoft" ], "interpretation": "Survival within these scenarios is not a confidence interval or proof that an untested competitor cannot enter.", "weightTests": "Function emphasis varies through explicit alternative sets; an additive weighted score is deliberately not fitted to incomparable inputs.", "estimateTests": "Remove private run rates or discount their comparability: commercial roles remain established, but precise ordinal comparisons become less supportable. No estimate is silently converted to fact.", "missingDataTests": "Oracle, Cloudera, Cisco and Alibaba explicitly enter alternative sets despite unavailable comparable current product revenue. Missing values remain null.", "universeTests": "Including cloud data products changes three seats versus the old list. Further plausible supplier entry can change the cutoff; private disclosure is not an exclusion rule." }, "changesVersusPrior": { "added": [ "alphabet", "amazon", "microsoft" ], "removed": [ "dynatrace", "elastic", "grafana-labs" ], "retained": [ "databricks", "datadog", "fivetran", "ibm", "mongodb", "palantir", "snowflake" ], "removedDisposition": "All removed baseline companies retain their researched dossiers and are visible alternatives; removal reflects limited representative slots, not a negative commercial conclusion." }, "limitations": [ "The evidence does not identify a unique ordered global Top 10. Publishing ordinal ranks would overstate the method.", "Five required functions and a ten-company ceiling are editorial decisions. Fivetran versus a second incumbent database supplier and the observability representative are particularly contestable.", "Private run rates are company statements; public revenue includes substantial conventional data workloads. No global AI-attribution fractions are invented.", "Customer, account and developer definitions differ. A provider customer can itself serve millions of users; those user counts are not supplier customers.", "Observed supplier universe is broad but not exhaustive. Current revenue is unavailable for several eligible large suppliers." ], "refresh": "Monitor current sources daily; reconsider universe quarterly. Immediate changes follow acquisition completion, divestiture, product discontinuation or eligibility loss. Ordinary close-cutoff substitutions require sustained evidence across two reviews; preserve alternative sets and date every change.", "layer": "applications", "publicationInterpretation": "This is an evidence-backed representative selection. 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