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Comparison · Infra & APIs
Databricks vs Depot
A side-by-side editorial comparison of Databricks and Depot — release velocity, themes, recent moves, and the top alternatives to consider.
Databricks vs Depot: at a glance
| Feature | Databricks | Depot |
|---|---|---|
| Sector | Infra & APIs, Analytics | Infra & APIs |
| Velocity score | 5.0 | 6.3 |
| Sparks · 30d | 0 | 1 |
| Top themes | data-platform, spark-4, databricks-runtime, jdk-21 | ci-cd, build-acceleration, test-analytics, source-control |
| Last editorial update | 3mo ago | 1d ago |
| Website | Visit → | — |
What is Databricks?
Databricks lands DBR 18.2 GA on Spark 4.1; the 18.x line is the active story, older LTS pages are mostly doc refreshes.
The substantive shipping event in the window is Databricks Runtime 18.2 GA on May 4, the latest minor in a fast 18.x cadence on Spark 4.1.0 (18.0 in January, 18.1 in March, 18.2 Beta on April 8, GA on May 4). The rest of the recent feed is an April 13 documentation refresh that updated release notes for older LTS versions — 14.3, 15.4, 16.4, 17.3, 13.3 — without new shipping behind them.
What is Depot?
Depot is expanding from faster builds into the whole CI stack — tests, source control, and its own metal.
Depot has spent the last month building outward from build acceleration. Test results went generally available with JUnit ingest, org-wide flaky and slow test analytics, and timing-based shard balancing. Underneath that, Depot Metal moved CI and Sandboxes onto bare-metal microVMs the company controls end to end, and Depot Code entered private beta as a diskless git server backed by blob storage. The smaller releases fill in the surrounding surface: Tailscale access to private networks, GitLab OIDC, Datadog CI Visibility, stacked pull requests, and macOS 26 runners on M4.
Databricks vs Depot: editorial side-by-side
Databricks
5.0INFRA · APISANALYTICS
Databricks lands DBR 18.2 GA on Spark 4.1; the 18.x line is the active story, older LTS pages are mostly doc refreshes.
◆ Current state
The substantive shipping event in the window is Databricks Runtime 18.2 GA on May 4, the latest minor in a fast 18.x cadence on Spark 4.1.0 (18.0 in January, 18.1 in March, 18.2 Beta on April 8, GA on May 4). The rest of the recent feed is an April 13 documentation refresh that updated release notes for older LTS versions — 14.3, 15.4, 16.4, 17.3, 13.3 — without new shipping behind them.
◆ Where it's heading
Databricks is pushing Spark 4.1 hard through the runtime line: JDK 21 default in 18.x, breaking changes around NULL preservation and partition columns, aggressive deprecation of older behaviors (input_file_name removal, AWS SDK v1 shading). The 18.x cadence is roughly one minor every six weeks, and 16.4 LTS is acting as the bridge for customers needing to migrate Scala 2.12 code to 2.13 before they can move to 17 or 18.
◆ Prediction
Expect an 18.x LTS designation later in 2026 once the line stabilizes, with continued behavioral hardening and more shaded dependency cleanup. Doc refreshes for older LTS versions — particularly 13.3 LTS, which is close to its August 2026 end-of-support — will likely keep landing as Databricks pushes customers up the runtime stack.
Depot
6.3INFRA · APIS
Depot is expanding from faster builds into the whole CI stack — tests, source control, and its own metal.
◆ Current state
Depot has spent the last month building outward from build acceleration. Test results went generally available with JUnit ingest, org-wide flaky and slow test analytics, and timing-based shard balancing. Underneath that, Depot Metal moved CI and Sandboxes onto bare-metal microVMs the company controls end to end, and Depot Code entered private beta as a diskless git server backed by blob storage. The smaller releases fill in the surrounding surface: Tailscale access to private networks, GitLab OIDC, Datadog CI Visibility, stacked pull requests, and macOS 26 runners on M4.
◆ Where it's heading
Each layer Depot adds is one it previously rented — compute from cloud runners, source hosting from GitHub, test insight from nothing at all. Owning the storage and hypervisor tiers is what makes the performance claims possible, and owning test data is what turns a build accelerator into something that reports on the pipeline rather than just running it faster. The pattern suggests Depot is positioning as the full CI platform, with speed as the entry point rather than the product.
◆ Prediction
Depot Code should move from private to open beta with tighter Depot CI integration, since a git server the company controls is what makes source-aware caching and test selection possible. Expect the test analytics to grow toward selecting which tests to run, not only how to split them.
Alternatives to Databricks and Depot
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Databricks or Depot.
werf
Four channels, one fix stream — werf's releases are mostly concurrency repairs.
ZoneMinder
1.38.4 is a security release in all but name, closing ACL gaps across the API.
Infisical
PAM and PKI now take up most of the lines in Infisical's release notes.
Biome
Biome's patch train keeps adding rules — and is quietly growing a Markdown linter.
DNSControl
DNSControl is rewriting its record internals in public, one release candidate at a time
See all Databricks alternatives → · See all Depot alternatives →
Recent activity from Databricks and Depot
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoDepotmacOS 26 is now the default macOS version for GitHub Actions runners
- 8d agoDepotDepot CI now supports native GitHub stacked pull requests
- 13d agoDepotTest results are now generally available ⚡
- 21d agoDepotAI analysis available for all Depot CI workflows and jobs
- 27d agoDepotSplit CI test suites with historical timing data (beta)
- 1mo agoDepotDepot CI now supports Tailscale
- 3mo agoDatabricksDatabricks Runtime 18.2 (released May 4, 2026)
- 4mo agoDatabricksDBR 18.0 documentation refresh
- 4mo agoDatabricksDatabricks Runtime 15.4 LTS Databricks Runtime 15.4 LTS for Machine Learning 3.5.0Aug 19, 2024Aug 19, 2027
- 4mo agoDatabricksDatabricks Runtime 13.3 LTS Databricks Runtime 13.3 LTS for Machine Learning 3.4.1Aug 22, 2023Aug 22, 2026
- 4mo agoDatabricksDatabricks Runtime 17.3 LTS Databricks Runtime 17.3 LTS for Machine Learning 4.0.0Oct 22, 2025Oct 22, 2028
- 4mo agoDatabricksDatabricks Runtime 18.2 (Beta) Databricks Runtime 18.2 for Machine Learning (Beta) 4.1.0Apr 8, 2026Oct 8, 2026
Frequently asked questions
What is the difference between Databricks and Depot?
They serve adjacent needs but don't currently overlap on shipped themes. Depot is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Databricks better than Depot?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Depot is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to Databricks?
Top Databricks alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Databricks alternatives" section above for the current picks, or visit /alternatives/databricks for the full list with editorial commentary on each.
What are the best alternatives to Depot?
Top Depot alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Depot alternatives" section above for the current picks, or visit /alternatives/depot for the full list with editorial commentary on each.