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Comparison · Analytics
Klipfolio vs Dagster
A side-by-side editorial comparison of Klipfolio and Dagster — release velocity, themes, recent moves, and the top alternatives to consider.
Klipfolio vs Dagster: at a glance
What is Klipfolio?
Dashboard analytics in slow maintenance, with admin controls the only moving part
The recent record is thin and heavily duplicated — each change appears two or three times, once with a mangled title carrying the body text. What actually shipped: a custom-role permission letting admins delegate viewer management, MFA device memory with an admin-enforced requirement, and API key access. The newest item is dated March.
What is Dagster?
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.
Klipfolio vs Dagster: editorial side-by-side
Klipfolio
0.0ANALYTICS
Dashboard analytics in slow maintenance, with admin controls the only moving part
◆ Current state
The recent record is thin and heavily duplicated — each change appears two or three times, once with a mangled title carrying the body text. What actually shipped: a custom-role permission letting admins delegate viewer management, MFA device memory with an admin-enforced requirement, and API key access. The newest item is dated March.
◆ Where it's heading
Development is concentrated on account administration rather than the analytics surface. Delegating viewer management and enforcing MFA are the concerns of a product whose growth comes from agencies and self-managed client accounts, where the buyer administers many downstream users. No dashboard, data-source or visualization work appears in the window at all.
◆ Prediction
The entries show four months without a release and no product-surface work, so there is nothing here to support a confident prediction about what ships next.
Dagster
5.0ANALYTICS
Dagster drops Python 3.10 and lets agents run schedules and sensors through MCP.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to Klipfolio and Dagster
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 Klipfolio or Dagster.
Dovetail
Dovetail lets admins choose which connectors members can plug into the workspace.
OpenHouse
OpenHouse adds time-zone-aware retention and per-database table caps.
Countly
Countly 25.03.59 defaults to Node 26, supports MongoDB 9 and tightens app scoping.
Kubecost
Kubecost cuts three 3.3.2 release candidates in two days, still without notes.
RStudio
RStudio opens the 2026.11 train with another NOTICE file update.
See all Klipfolio alternatives → · See all Dagster alternatives →
Recent activity from Klipfolio and Dagster
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoDagster1.13.30: Python 3.11 minimum, more Dagster+ MCP tools
- 8d agoDagster1.13.29: more mobile layouts, faster search and catalog
- 14d agoDagster1.13.28: dbt v2 extra and retries for failed code locations
- 18d agoDagster1.13.27: mobile run details, bounded BigQuery Insights scans
- 1mo agoDagster1.13.26: dagster-dbt stops installing dbt-core
- 1mo agoDagster1.13.25: phone layout for the Dagster UI, ECS run resumes
- 8mo agoKlipfolioNew permission for custom roles
- 8mo agoKlipfolioNew permission for custom roles
- 8mo agoKlipfolioDuplicate record of the custom-role permission
- 10mo agoKlipfolioEnhanced security
- 10mo agoKlipfolioDuplicate record of the MFA change
- 11mo agoKlipfolioNew and improved billing system
Frequently asked questions
What is the difference between Klipfolio and Dagster?
They serve adjacent needs but don't currently overlap on shipped themes. 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.
Is Klipfolio better than Dagster?
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.
What are the best alternatives to Klipfolio?
Top Klipfolio alternatives in Analytics are ranked by recent ship velocity. Browse the "Klipfolio alternatives" section above for the current picks, or visit /alternatives/klipfolio for the full list with editorial commentary on each.
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.