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Comparison · Analytics
dbt Core vs Deepnote
A side-by-side editorial comparison of dbt Core and Deepnote — release velocity, themes, recent moves, and the top alternatives to consider.
dbt Core vs Deepnote: at a glance
| Feature | dbt Core | Deepnote |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 7.5 | 6.3 |
| Sparks · 30d | 2 | 0 |
| Top themes | dbt-fusion, rust-rewrite, static-analysis, semantic-layer | data notebooks, agentic ai, mcp, reproducibility |
| Last editorial update | 22h ago | 1mo ago |
| Website | Visit → | — |
What is dbt Core?
The Rust rewrite crosses from alpha to beta, and it can now bind SQL without touching the warehouse.
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
What is Deepnote?
Deepnote reshapes the data notebook into agent-operable infrastructure.
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
dbt Core vs Deepnote: editorial side-by-side
dbt Core
7.5ANALYTICS
The Rust rewrite crosses from alpha to beta, and it can now bind SQL without touching the warehouse.
◆ Current state
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
◆ Where it's heading
Fusion is being built to do statically what dbt-core did by asking the warehouse. Catalog-free binding lets SQL bind without introspection, tests get skipped when they are provably redundant, and dbt State speculatively submits nodes while the dependency prefetch is still in flight — all of it trading round-trips for compile-time analysis. Meanwhile 1.x is absorbing the v2 semantic layer YAML piece by piece, which puts metrics and entities into the model graph itself. Adapter breadth keeps widening in parallel, with Databricks service principal auth, Redshift group grants, and ClickHouse materialization configs.
◆ Prediction
With beta.1 out, the next milestones are further betas hardening the Fusion feature set toward parity, and continued v2 semantic YAML work landing in the 1.x line.
Deepnote
6.3ANALYTICS
Deepnote reshapes the data notebook into agent-operable infrastructure.
◆ Current state
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
◆ Where it's heading
Two tracks are converging: reproducibility and engineering rigor (immutable run snapshots, Git sync, notebook interoperability) and agent-operability (MCP tools, Codex context). Deepnote is positioning the workspace as the trusted context layer that AI agents act through, not just a place humans write notebooks.
◆ Prediction
Expect more MCP tooling that lets agents operate Deepnote projects autonomously, plus deeper native hooks for external coding agents — the workspace-as-agent-context bet will likely expand beyond Codex.
Alternatives to dbt Core and Deepnote
Other Analytics 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 dbt Core or Deepnote.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature
OpenDataDiscovery
Four ODD Platform releases in two weeks, and not one of them changes the product
Apache Baremaps
Baremaps got geoparquet and hillshading, then went quiet for eighteen months in incubation
Deequ
Deequ ships GitHub tags whose release notes are one commit message long
Marquez
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
See all dbt Core alternatives → · See all Deepnote alternatives →
Recent activity from dbt Core and Deepnote
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agodbt Coredbt Fusion 2.0 reaches first beta with catalog-free SQL binding ⚡
- 22d agodbt Corev2.0.0-alpha.5
- 26d agodbt Coredbt-core v1.12.0 ⚡
- 28d agodbt Coredbt-core v1.12.0rc3
- 1mo agodbt Coredbt-core v1.12.0rc2
- 1mo agodbt Coredbt-core v1.12.0rc1
- 1mo agoDeepnoteNew MCP tools for integrations
- 2mo agoDeepnoteYour workspace as the context for every exploration ⚡
- 3mo agoDeepnoteRun snapshots, Git sync, & AI usage visibility
- 3mo agoDeepnoteRun snapshots, Git sync, Polars support, PDF export, & a cleaner notebook
- 3mo agoDeepnoteRun snapshots, Git sync, Polars support, PDF export, & a cleaner notebook
- 4mo agoDeepnotePolars support, PDF export & a cleaner notebook
Frequently asked questions
What is the difference between dbt Core and Deepnote?
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 7.5 vs 6.3), with 2 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 dbt Core better than Deepnote?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 7.5 vs 6.3), with 2 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to dbt Core?
Top dbt Core alternatives in Analytics are ranked by recent ship velocity. Browse the "dbt Core alternatives" section above for the current picks, or visit /alternatives/dbt-core for the full list with editorial commentary on each.
What are the best alternatives to Deepnote?
Top Deepnote alternatives in Analytics are ranked by recent ship velocity. Browse the "Deepnote alternatives" section above for the current picks, or visit /alternatives/deepnote for the full list with editorial commentary on each.