OpenMetadata
MCP servers became first-class governed assets in 1.13.0 — and 2.0 is now in release candidate.
Comparison · Analytics
Dagster vs Mage
A side-by-side editorial comparison of Dagster and Mage — release velocity, themes, recent moves, and the top alternatives to consider.
Dagster vs Mage: at a glance
What is Dagster?
Dagster's declarative automation engine just learned to trigger jobs, not only assets.
Dagster ships a core release weekly on a tight 1.13.x cadence, with most weeks split between component integrations and UI performance work. Two threads dominate the last two months: Declarative Automation as the scheduling model, and Components as the packaging model for integrations — dbt, Snowflake, dlt, Fivetran each arriving as a configurable component rather than bespoke wiring. The 1.13.16 release connects the first thread to jobs, a primitive that had been outside the declarative model.
What is Mage?
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 vs Mage: editorial side-by-side
Dagster
6.3ANALYTICS
Dagster's declarative automation engine just learned to trigger jobs, not only assets.
◆ Current state
Dagster ships a core release weekly on a tight 1.13.x cadence, with most weeks split between component integrations and UI performance work. Two threads dominate the last two months: Declarative Automation as the scheduling model, and Components as the packaging model for integrations — dbt, Snowflake, dlt, Fivetran each arriving as a configurable component rather than bespoke wiring. The 1.13.16 release connects the first thread to jobs, a primitive that had been outside the declarative model.
◆ Where it's heading
The direction is a platform where orchestration is declared as conditions over data, and integrations are assembled from YAML-configurable components instead of Python glue. Supporting moves point the same way: dg tooling hardening, an MCP server for agent access, and a Components tab that now enumerates every instance in a code location. Alongside this, a steady stream of virtualization and bounded-fetch work in the UI signals that large deployments — thousands of assets, many backfills — are the deployments Dagster is now optimizing for.
◆ Prediction
Expect the job-level automation conditions to move from preview toward general availability, and more first-party integrations to be re-released as components. The entries do not show which integration is next in that queue.
Mage
0.0ANALYTICS
Feature releases every two months in 2024; one bugfix release in the last twelve.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to Dagster and Mage
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.
TimescaleDB
Every release in this window is columnstore work — compression is where TimescaleDB is spending
Polars
The streaming engine is stable and the API is being narrowed — Polars is clearing ground for a breaking release
DuckDB
Six releases, all patches — this window shows DuckDB's maintenance machine, not its roadmap
dbt Core
Two engines in one repo: the Python 1.x line tightens while Fusion 2.0 goes lakehouse-catalog native
Basedash
Basedash turned its AI analyst into an API, then spent two weeks making it auditable
See all Dagster alternatives → · See all Mage alternatives →
Recent activity from Dagster and Mage
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoDagsterDeclarative Automation can now trigger jobs ⚡
- 8d agoDagsterSnowflake dbt projects get a native component
- 15d agoDagsterServerless I/O manager error fixes
- 22d agoDagsterInstall dependency and automation tick fixes
- 29d agoDagsterRuns feed goes bounded; automation tick halt fixed
- 1mo agoDagsterVirtualized asset catalog; dbt insights from YAML
- 6mo agoMageDependency pinning and SQLAlchemy 2.0 compatibility fixes
- 11mo agoMagePath traversal CVE fixes and cancellation callbacks
- 1y agoMageTeradata, Doris and Airtable connectors, rotatable API tokens
- 1y agoMageAirtable destination and Python 3.11 and 3.12 support
- 1y agoMageGoogle Cloud Storage source and Airtable integration
- 1y agoMageMemory management rework and dynamic blocks 2.0
Frequently asked questions
What is the difference between Dagster and Mage?
They serve adjacent needs but don't currently overlap on shipped themes. Dagster is currently shipping more aggressively (velocity 6.3 vs 0.0), 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 Dagster better than Mage?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Dagster is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 Dagster?
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.
What are the best alternatives to Mage?
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.