Mage
Feature releases every two months in 2024; one bugfix release in the last twelve.
A side-by-side editorial comparison of Tinybird and dbt Core — release velocity, themes, recent moves, and the top alternatives to consider.
Tinybird is walking users off Classic one default flip at a time.
Tinybird ships a dated roundup roughly weekly, and the through-line is a platform migration from Classic to Forward. v1 ingestion went from experimental in the CLI to the default for local files inside a week, Classic is being sunset for Free and Developer plans by September 15, and connector work like DynamoDB is landing in Forward rather than Classic.
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.
Tinybird ships a dated roundup roughly weekly, and the through-line is a platform migration from Classic to Forward. v1 ingestion went from experimental in the CLI to the default for local files inside a week, Classic is being sunset for Free and Developer plans by September 15, and connector work like DynamoDB is landing in Forward rather than Classic.
The migration is being executed by moving defaults and withdrawing plans rather than by announcement — each release makes the new path slightly more automatic and the old one slightly less supported. Underneath it the data plane keeps hardening: lightweight deletes, native arm64 for Tinybird Local, a ClickHouse bump from 25.3 to 25.8, correct integer handling in JSON ingestion. Agent skills now appear in the release notes too, alongside deployment-progress and backfill job plumbing.
Expect further Classic capabilities to be withheld from new work and more defaults to flip toward v1 ahead of the September 15 sunset. Whether paid tiers face the same Classic deadline is not stated in these entries.
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.
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.
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.
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 Tinybird or dbt Core.
Feature releases every two months in 2024; one bugfix release in the last twelve.
MCP servers became first-class governed assets in 1.13.0 — and 2.0 is now in release candidate.
Every release in this window is columnstore work — compression is where TimescaleDB is spending
The streaming engine is stable and the API is being narrowed — Polars is clearing ground for a breaking release
Six releases, all patches — this window shows DuckDB's maintenance machine, not its roadmap
Basedash turned its AI analyst into an API, then spent two weeks making it auditable
See all Tinybird alternatives → · See all dbt Core alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 7.5 vs 5.0), 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 7.5 vs 5.0), 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.
Top Tinybird alternatives in Analytics are ranked by recent ship velocity. Browse the "Tinybird alternatives" section above for the current picks, or visit /alternatives/tinybird for the full list with editorial commentary on each.
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.