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Comparison · Analytics
dbt Core vs Omni
A side-by-side editorial comparison of dbt Core and Omni — release velocity, themes, recent moves, and the top alternatives to consider.
dbt Core vs Omni: at a glance
What is dbt Core?
Two engines in one repo: the Python 1.x line tightens while Fusion 2.0 goes lakehouse-catalog native
dbt-core is releasing on two tracks at once. The Python line reached 1.12.0 on 16 July after three release candidates, and it is a tightening release: the experimental `dbt login` command and the bundled dbt-state plugin were removed outright, and flags introduced in 1.9 and 1.10 now default to true. The 2.0.0 alpha track is the Fusion engine, and its work is almost entirely about catalogs — read-write Horizon and Unity access over Iceberg REST via DuckDB, a catalogs.yml v2 covering DuckLake, Iceberg REST and local filesystem, plus catalog_database overrides and Redshift catalog generation through SHOW TABLES and SVV_REDSHIFT_COLUMNS.
What is Omni?
Omni ships weekly, and this quarter every week added something to the AI layer.
Omni publishes a dated digest every week, each bundling a handful of unrelated changes. Across the current window the AI work is continuous rather than occasional: AI Hub and Markdown columns reached general availability in May, visualization annotations in June, semantic model generation in July, with AI Routines gaining Slack support and chat-based creation along the way. The non-AI half is connection and embedding plumbing — OAuth for database connections, GitHub App and HTTPS deploy-token authentication for dbt, AccessBoost for Apps, embed display and timezone controls.
dbt Core vs Omni: editorial side-by-side
dbt Core
7.5ANALYTICS
Two engines in one repo: the Python 1.x line tightens while Fusion 2.0 goes lakehouse-catalog native
◆ Current state
dbt-core is releasing on two tracks at once. The Python line reached 1.12.0 on 16 July after three release candidates, and it is a tightening release: the experimental `dbt login` command and the bundled dbt-state plugin were removed outright, and flags introduced in 1.9 and 1.10 now default to true. The 2.0.0 alpha track is the Fusion engine, and its work is almost entirely about catalogs — read-write Horizon and Unity access over Iceberg REST via DuckDB, a catalogs.yml v2 covering DuckLake, Iceberg REST and local filesystem, plus catalog_database overrides and Redshift catalog generation through SHOW TABLES and SVV_REDSHIFT_COLUMNS.
◆ Where it's heading
The division of labour between the two tracks is clear from the entries: 1.x is consolidating and removing experiments, while 2.0 is where the new surface area lands. The 2.0 surface is specifically the lakehouse catalog layer — dbt is moving from a tool that writes to a warehouse toward one that binds to open table catalogs directly, with materialization made catalog-aware. Notably 1.12.0rc1 also teaches the Python engine to tolerate Fusion-specific warn_error_options rather than erroring, so the two engines are being made to coexist in the same projects rather than fork.
◆ Prediction
The alphas are still expanding catalog coverage adapter by adapter, so expect further catalog integrations and continued catalogs.yml v2 work before 2.0 leaves alpha. On the Python side, with the deprecated flags now defaulted and the experimental commands removed, 1.12 looks like a stabilization point rather than a base for new features.
Omni
6.3ANALYTICS
Omni ships weekly, and this quarter every week added something to the AI layer.
◆ Current state
Omni publishes a dated digest every week, each bundling a handful of unrelated changes. Across the current window the AI work is continuous rather than occasional: AI Hub and Markdown columns reached general availability in May, visualization annotations in June, semantic model generation in July, with AI Routines gaining Slack support and chat-based creation along the way. The non-AI half is connection and embedding plumbing — OAuth for database connections, GitHub App and HTTPS deploy-token authentication for dbt, AccessBoost for Apps, embed display and timezone controls.
◆ Where it's heading
Omni is putting AI underneath the modeling layer rather than beside the charts. Generating the semantic model is a different bet than generating a query: the semantic layer is where a BI tool encodes what its metrics mean, and automating it moves AI from answering questions to defining the vocabulary the answers use. The governance work is arriving in step — AI credit controls per embed entity group and per user, AI skills gated by required access grants, evals support — which is what a vendor builds when customers are embedding these features into products they resell.
◆ Prediction
Expect AI Routines to keep expanding their trigger surface after Slack and chat-based creation, and the credit controls to grow into fuller usage governance as embedded AI reaches more end users. The digest format means individually significant launches will keep arriving in the middle of a list of unrelated fixes.
Alternatives to dbt Core and Omni
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 Omni.
Delta Lake
Delta Lake is handing table authority to Unity Catalog — under a feed buried in Databricks build tags.
OpenCTI
OpenCTI ships weekly and is rebuilding its connector catalog into a marketplace.
Grafana Mimir
Mimir's feed is mostly bot-authored Helm bumps; the real release is 3.2, and it is query-engine work.
Fluent Bit
Fluent Bit runs a 4.2 and a 5.0 train side by side, both fed by the same backport pipeline.
Countly
Countly's core is in maintenance while every real feature lands in the enterprise journey engine.
See all dbt Core alternatives → · See all Omni alternatives →
Recent activity from dbt Core and Omni
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20h agoOmniAI credit controls for embeds, Evals on Azure
- 7d agoOmniAI semantic model generation reaches general availability ⚡
- 14d agoOmniAI model suggestion endpoints and database OAuth
- 15d agodbt CoreFusion alpha 5: Redshift datasharing catalogs and job-specific deferral
- 18d agodbt Coredbt-core 1.12.0 drops `dbt login` and the dbt-state plugin ⚡
- 20d agodbt Core1.12.0 release candidate 3
- 21d agoOmniAI Routines reach Slack, MCP settings move in-app
- 25d agodbt Core1.12.0 release candidate 2
- 28d agodbt Core1.12.0 release candidate 1
- 28d agoOmniAccessBoost for Apps and dbt deploy-token auth
- 29d agodbt CoreFusion gains read-write Iceberg REST catalogs and catalogs.yml v2 ⚡
- 1mo agoOmniAI visualization annotations GA, apps on by default
Frequently asked questions
What is the difference between dbt Core and Omni?
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 1. 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 Omni?
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 1. 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 Omni?
Top Omni alternatives in Analytics are ranked by recent ship velocity. Browse the "Omni alternatives" section above for the current picks, or visit /alternatives/omni for the full list with editorial commentary on each.