# The most used data warehouse and pipeline tools As of October 2026, the most used of the 25 data warehouse and pipeline tools runsonwhat tracks is Adobe Experience Platform Tags, found at 10,152 companies, ahead of Tealium (3,043) and Treasure Data (1,494). The modern data stack runs from ingestion (Fivetran, Confluent) to a warehouse or lakehouse (Snowflake, Databricks, ClickHouse), through transformation (dbt), out to business tools with reverse ETL (Census, Hightouch), and into dashboards (Looker, Metabase, Hex, Apache Superset). Data tools are mostly internal, so they appear in public records less often than website tools. The companies listed here are ones where a verification record, a subdomain or a subprocessor list names the vendor. ## Data warehouse and pipeline tools ranked by companies using them | # | Tool | Companies | Share of category | Last 30 days | Most popular with | |---|---|---|---|---|---| | 1 | [Adobe Experience Platform Tags](https://www.runsonwhat.com/reverse/adobe-launch) | 10,152 | 55% | +6 | Automotive (14×) | | 2 | [Tealium](https://www.runsonwhat.com/reverse/tealium) | 3,043 | 17% | +2 | 10,000+ employees (8.7×) | | 3 | [Treasure Data](https://www.runsonwhat.com/reverse/treasure-data) | 1,494 | 8.1% | – | Automotive (19×) | | 4 | [BlueConic](https://www.runsonwhat.com/reverse/blueconic) | 678 | 3.7% | – | Veterinary (125×) | | 5 | [mParticle](https://www.runsonwhat.com/reverse/mparticle) | 459 | 2.5% | – | Non-profit Organization Management (15×) | | 6 | [Metabase](https://www.runsonwhat.com/reverse/metabase) | 429 | 2.3% | +1 | 1–10 employees (15×) | | 7 | [Salesforce Audience Studio](https://www.runsonwhat.com/reverse/salesforce-audience-studio) | 366 | 2.0% | +1 | Sports (24×) | | 8 | [Astronomer](https://www.runsonwhat.com/reverse/astronomer) | 262 | 1.4% | +2 −2 | 10,000+ employees (21×) | | 9 | [Lytics](https://www.runsonwhat.com/reverse/lytics) | 227 | 1.2% | – | 51–200 employees (1.6×) | | 10 | [Snowflake](https://www.runsonwhat.com/reverse/snowflake) | 225 | 1.2% | +7 | 10,000+ employees (18×) | | 11 | [Oracle BlueKai](https://www.runsonwhat.com/reverse/oracle-bluekai) | 179 | 0.97% | – | Newspapers (96×) | | 12 | [Squeezely](https://www.runsonwhat.com/reverse/squeezely) | 155 | 0.84% | – | Retail (6.6×) | | 13 | [Apache Superset](https://www.runsonwhat.com/reverse/superset) | 135 | 0.73% | −1 | – | | 14 | [Confluent](https://www.runsonwhat.com/reverse/confluent) | 117 | 0.64% | +2 −1 | – | | 15 | [Apache Airflow](https://www.runsonwhat.com/reverse/airflow) | 107 | 0.58% | – | – | | 16 | [Optimove](https://www.runsonwhat.com/reverse/optimove) | 105 | 0.57% | – | – | | 17 | [ClickHouse](https://www.runsonwhat.com/reverse/clickhouse) | 78 | 0.42% | +3 | – | | 18 | [Matillion](https://www.runsonwhat.com/reverse/matillion) | 76 | 0.41% | +18 | – | | 19 | [Looker](https://www.runsonwhat.com/reverse/looker) | 59 | 0.32% | – | – | | 20 | [Databricks](https://www.runsonwhat.com/reverse/databricks) | 27 | 0.15% | – | – | | 21 | [Fivetran](https://www.runsonwhat.com/reverse/fivetran) | 22 | 0.12% | – | – | | 22 | [dbt Labs](https://www.runsonwhat.com/reverse/dbt) | 6 | <0.1% | – | – | | 23 | [Hightouch](https://www.runsonwhat.com/reverse/hightouch) | 4 | <0.1% | – | – | | 24 | [Hex](https://www.runsonwhat.com/reverse/hex) | 1 | <0.1% | – | – | Share is each tool's part of all 18,406 matches in this category; a company using two tools counts for both. ## How to compare data warehouse and pipeline tools - Warehouse pricing: compute credits versus provisioned clusters. - Connector coverage for the sources you actually use. - Where transformation happens and who owns it. - Governance: access control, lineage and data residency. ## How runsonwhat finds data warehouse and pipeline tools Data tools show up in domain-verification records, in internal hostnames found in certificate logs (metabase.example.com), in subdomains pointing at the vendor and on subprocessor lists. Also tracked, no confirmed customers yet: Census. ## FAQ ### What are the most popular data warehouse and pipeline tools? As of October 2026, the most popular data warehouse and pipeline tools by number of companies using them are Adobe Experience Platform Tags (10,152 companies), Tealium (3,043 companies) and Treasure Data (1,494 companies), according to runsonwhat. Adobe Experience Platform Tags alone accounts for 55% of the 18,406 Data Pipeline matches runsonwhat has, and the top three together for 80%. 24 data warehouse and pipeline tools have at least one confirmed customer. ### Adobe Experience Platform Tags vs Tealium: which is more popular? Adobe Experience Platform Tags is more popular: 10,152 companies show public evidence of Adobe Experience Platform Tags, against 3,043 for Tealium (3.3× as many), according to runsonwhat (October 2026). Treasure Data is third with 1,494. ### Which data warehouse and pipeline tools do small businesses use most? Among companies with up to 50 employees, the most used data warehouse and pipeline tools are Adobe Experience Platform Tags (2,562 companies), Tealium (937 companies) and Treasure Data (422 companies), according to runsonwhat (October 2026). The counts cover companies with a known headcount; see each tool's page for the full size breakdown. ### Which data warehouse and pipeline tools do large companies use most? Among companies with more than 1,000 employees, the most used data warehouse and pipeline tools are Adobe Experience Platform Tags (1,419 companies), Tealium (396 companies) and Astronomer (92 companies), according to runsonwhat (October 2026). Large companies often run more than one tool in a category, so the same company can count for several. ### Which data warehouse and pipeline tools are most popular in the United States? In the United States, the most used data warehouse and pipeline tools are Adobe Experience Platform Tags (5,034 companies), Tealium (1,542 companies) and Treasure Data (449 companies), based on companies runsonwhat has located there (October 2026). Adobe Experience Platform Tags has 59% of the Data Pipeline matches among companies based in the United States. ### Which data warehouse and pipeline tools are most popular in Japan? In Japan, the most used data warehouse and pipeline tools are Treasure Data (676 companies), Adobe Experience Platform Tags (181 companies) and Tealium (21 companies), based on companies runsonwhat has located there (October 2026). Treasure Data has 75% of the Data Pipeline matches among companies based in Japan. ### Which data warehouse and pipeline tools do automotive companies use? Automotive is the industry with the most Data Pipeline matches, and its companies use Adobe Experience Platform Tags (1,559 companies), Treasure Data (240 companies) and Tealium (228 companies) most, according to runsonwhat (October 2026). Each tool's page breaks its customers down by industry, so you can check where a tool over-indexes. ### Which data warehouse and pipeline tools are companies adopting right now? In the 30 days to October 2026, the most new adoptions runsonwhat recorded were for Matillion (18 companies), Snowflake (7 companies) and Adobe Experience Platform Tags (6 companies). A start is counted when a recheck finds a tool that the previous check of the same company, done the same way, did not. ### What is Adobe Experience Platform Tags' market share among data warehouse and pipeline tools? Adobe Experience Platform Tags has 55% of the Data Pipeline matches runsonwhat has found (10,152 companies of 18,406), as of October 2026; Tealium has 17%. This is share of companies with public evidence of each tool, not share of revenue or seats, and a company that runs two tools counts for both. ### How does runsonwhat rank data warehouse and pipeline tools? runsonwhat counts the companies where a public record shows each tool in use and ranks by that count. Data tools show up in domain-verification records, in internal hostnames found in certificate logs (metabase.example.com), in subdomains pointing at the vendor and on subprocessor lists. A company counts only when a direct record backs it up. The full method is at https://www.runsonwhat.com/methodology. ## Related categories - [Monitoring](https://www.runsonwhat.com/tools/monitoring.md) - [Analytics](https://www.runsonwhat.com/tools/analytics.md) - [Flags & Experiments](https://www.runsonwhat.com/tools/feature-flags-ab-testing.md) --- Source: runsonwhat, https://www.runsonwhat.com/tools/data-pipelines (updated October 2026). Counts are companies with direct public evidence of the tool (DNS records, certificates, website code, a real-browser crawl, subprocessor lists), so they are lower bounds. Methodology: https://www.runsonwhat.com/methodology.