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A side-by-side editorial comparison of Dagster and Mage — release velocity, themes, recent moves, and the top alternatives to consider.
Dagster drops Python 3.10 and lets agents run schedules and sensors through MCP.
Dagster's 1.13 line ships weekly and follows two threads. dagster-dbt no longer installs dbt-core and gained a dbt v2 extra for the Fusion engine, while the UI keeps getting phone layouts and faster search and catalog pages. 1.13.30 on November 12 makes Python 3.11 the minimum and widens the Dagster+ MCP server to reading and toggling schedules and sensors and managing partitions.
Feature releases every two months in 2024; one bugfix release in the last twelve.
The release cadence has collapsed. Through 2024 Mage shipped roughly every two months with substantial features each time — memory management rework, dynamic blocks, new sources and destinations, Python 3.11 and 3.12 support. 2025 produced two releases. The most recent entry, 0.9.79 in January 2026, contains no feature section at all: it is dependency pinning, SQLAlchemy 2.0 compatibility, character escaping during code interpolation, and log file handle cleanup. Nothing has followed it in the six months since.
Dagster's 1.13 line ships weekly and follows two threads. dagster-dbt no longer installs dbt-core and gained a dbt v2 extra for the Fusion engine, while the UI keeps getting phone layouts and faster search and catalog pages. 1.13.30 on November 12 makes Python 3.11 the minimum and widens the Dagster+ MCP server to reading and toggling schedules and sensors and managing partitions.
The Dagster+ MCP server has grown release by release, from launching runs without a code location in September to controlling schedules, sensors and partitions now. Combined with the dbt split, Dagster is trimming legacy dependencies while making the orchestrator something an agent can operate, not just a person in the UI.
The MCP server still lacks write access to things like backfills and alert policies, so expanding it there is the most visible next step; further Python and dbt version floors are likely to follow the 3.10 cut.
The release cadence has collapsed. Through 2024 Mage shipped roughly every two months with substantial features each time — memory management rework, dynamic blocks, new sources and destinations, Python 3.11 and 3.12 support. 2025 produced two releases. The most recent entry, 0.9.79 in January 2026, contains no feature section at all: it is dependency pinning, SQLAlchemy 2.0 compatibility, character escaping during code interpolation, and log file handle cleanup. Nothing has followed it in the six months since.
The arc runs from expanding the product to keeping it compiling. The 2024 releases added capability — a canvas rework, multi-project support, streaming sinks, Kubernetes job parameters. The 2025 releases shifted toward integrations and CVE response, including a batch of path traversal fixes carrying assigned identifiers. The last release is entirely defensive, including vendoring croniter into the repository and locking scikit-learn to stop upstream changes from breaking builds. That is the profile of a codebase being kept viable rather than developed.
The entries give no basis for predicting the next release — a six-month gap after a dependency-only patch is the only signal available, and nothing here indicates whether the line is paused or finished.
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 Dagster or Mage.
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OpenMetadata 2.0.8 widens Hex, Sigma and BigQuery coverage while 2.1 waits in release candidates.
Dovetail lets admins choose which connectors members can plug into the workspace.
OpenHouse adds time-zone-aware retention and per-database table caps.
Countly 25.03.59 defaults to Node 26, supports MongoDB 9 and tightens app scoping.
Kubecost cuts three 3.3.2 release candidates in two days, still without notes.
See all Dagster alternatives → · See all Mage alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — orchestration — within Analytics. Dagster is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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. Dagster is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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 Dagster alternatives in Analytics are ranked by recent ship velocity. Browse the "Dagster alternatives" section above for the current picks, or visit /alternatives/dagster for the full list with editorial commentary on each.
Top Mage alternatives in Analytics are ranked by recent ship velocity. Browse the "Mage alternatives" section above for the current picks, or visit /alternatives/mage-ai for the full list with editorial commentary on each.