qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
constants vs Dagster
A side-by-side editorial comparison of constants and Dagster — release velocity, themes, recent moves, and the top alternatives to consider.
constants vs Dagster: at a glance
What is constants?
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
What is Dagster?
Dagster is turning declarative automation from an asset feature into the way the whole platform schedules work.
Dagster ships a core/libraries pair on a near-weekly cadence, and the release notes read like an engineering log: a few genuinely new capabilities per version, a long bugfix tail, and steady community contributions. The current cycle is concentrated in three places — Declarative Automation, the dbt-on-Snowflake integration, and asset health reporting. Serverless and Kubernetes deployment paths get frequent hardening.
constants vs Dagster: editorial side-by-side
constants
0.0ANALYTICS
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
◆ Current state
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
◆ Where it's heading
The direction set at 1.0.0 was to stop being a curated convenience wrapper and become a mechanical mirror of NIST. Hand-crafted symbol names were replaced with NIST's own ASCII symbols, categories adopted NIST's, and uncertainty switched from relative to absolute — all framed by the maintainer as necessary to make future CODATA updates routine. On top of that the package gained a correlation matrix and optional integration with the quantities package, moving it from a lookup table toward something that can propagate uncertainty.
◆ Prediction
Having rebuilt the symbol table specifically so CODATA revisions become mechanical, the next substantive release most likely tracks a new CODATA dataset rather than adding API. The experimental correlated-value support, disabled by default at 1.0.0, is the one part these entries flag as unfinished.
Dagster
6.3ANALYTICS
Dagster is turning declarative automation from an asset feature into the way the whole platform schedules work.
◆ Current state
Dagster ships a core/libraries pair on a near-weekly cadence, and the release notes read like an engineering log: a few genuinely new capabilities per version, a long bugfix tail, and steady community contributions. The current cycle is concentrated in three places — Declarative Automation, the dbt-on-Snowflake integration, and asset health reporting. Serverless and Kubernetes deployment paths get frequent hardening.
◆ Where it's heading
Declarative Automation is expanding past its original asset scope: it can now launch entire jobs from a condition, with its own evaluation history tab. In parallel, the component model is becoming the packaging unit for integrations, with SnowflakeDbtProjectComponent moving from preview toward parity with DbtCloudComponent via versioned state storage. Asset health is being made more honest — failures pending an automatic retry now warn rather than report degraded, so alerts stop crying wolf.
◆ Prediction
Declarative Automation for jobs is the clearest candidate to graduate from preview, and SnowflakeDbtProjectComponent is following the same preview-to-parity path. Expect the component surface to keep absorbing integrations that were previously bespoke code.
Alternatives to constants 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 constants or Dagster.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all constants alternatives → · See all Dagster alternatives →
Recent activity from constants and Dagster
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoDagsterPartition-level retry warnings and defs_state for the Snowflake dbt component
- 8d agoDagsterRetry-pending failures now warn instead of degrading
- 16d agoDagsterDeclarative Automation can now launch jobs (preview) ⚡
- 23d agoDagsterSnowflake dbt component preview and MCP server docs
- 1mo agoDagsterServerless I/O manager 401 and 400 errors fixed
- 1mo agoDagsterInstall-time protobuf version conflict fixed
- 5y agoconstantsCompatibility fix for units 0.7-0
- 5y agoconstantsconstants 1.0.0 ⚡
- 8y agoconstantsUnit handling fixes ahead of the 1.0.0 rebuild
Frequently asked questions
What is the difference between constants and Dagster?
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 constants better than Dagster?
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 constants?
Top constants alternatives in Analytics are ranked by recent ship velocity. Browse the "constants alternatives" section above for the current picks, or visit /alternatives/constants-r 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.