Comparison

Apache Spark vs Dagster

On the evidence we track, Dagster leads this comparison with a composite score of 70/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.

Machine formatsJSONMarkdownGraphQLor send Accept: application/json
Apache Spark61
Dagster70
Score
Vioscale score
Apache Spark61 / 100low · 38%
Dagster70 / 100medium · 68%
Pricing
Free tier
Apache Spark
Dagster
Model
Apache Sparkcommercial
Dagsterfreemium
Price level
Apache Sparkfree
Dagsterlow
Transparent
Apache Spark
Dagster
Integrations
Count
Apache Spark5
Dagster14
Adoption
Dependent repos
Apache Spark8,896
Dagster286
Github stars
Apache Spark43,882
Dagster16,066
Package downloads weekly
Apache Spark
Dagster2,176,853
Activity
Commits last 30d
Apache Spark100
Dagster81
Release
Cadence days
Apache Spark
Dagster7
History
Apache Spark
Dagster20 items
License
Spdx
Apache SparkApache-2.0
DagsterApache-2.0
Language
Primary
Apache SparkScala
DagsterPython
Market

Capabilities

Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.

Core
Tool role
Apache SparkProcessing engine
DagsterOrchestrator
Processing paradigm
Apache SparkBatch + streaming
DagsterBatch
Connectivity
Connector count
Apache Spark-
Dagster-
CDC / log-based replication
Apache Spark-
Dagster
Transformation
In-warehouse transformation (push-down)
Apache Spark-
Dagster
dbt-native orchestration
Apache Spark-
Dagster
Deployment
Self-hosted / open-source available
Apache Spark
Dagster
Managed cloud available
Apache Spark-
Dagster
Governance
Data lineage / asset catalog
Apache Spark-
Dagster
Authoring
Python-first authoring
Apache Spark-
Dagster
Execution
Incremental / partition-aware runs
Apache Spark-
Dagster
Quality
Built-in data quality / tests
Apache Spark-
Dagster
Scale
Horizontal scale (distributed executor)
Apache Spark
Dagster

What each one is

The product in its own terms, so the numbers below have context.

Apache Spark

Apache Spark is an open-source, multi-language distributed computing engine that unifies data engineering, data science, and machine learning workloads. It processes data at scale using batch or streaming paradigms, provides SQL query capabilities for analytics, and includes built-in libraries for machine learning and graph processing.

Independently observed

Dagster

Leader

A unified orchestration and observability platform that manages data pipelines through assets, tracks dependencies and lineage, enforces data quality, and integrates with existing tools like dbt, Snowflake, and Spark. Supports both self-hosted open-source and managed cloud deployment.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Apache Spark

Open sourceFree tier
as of verify ↗

Dagster

Leader
from $0.01/moSubscription30-day trial

From $120/month. 30-day free trial. Subscription with metered credits (asset materializations and ops executed); serverless compute charged separately.

  • Solo$120/month with 7.5k credits/month included; overages at $0.040/credit
    • 1 User
    • 1 Code location
    • 1 Deployment
    • Core orchestration
    • Asset-based orchestration
    • +6 more
  • Starter$1200/month with 30k credits/month included; overages at $0.035/credit
    • Up to 3 Users
    • 5 Code locations
    • 1 Deployment
    • Catalog search
    • Column-level lineage
    • +8 more
  • Pro/EnterpriseContact sales
    • Unlimited code locations
    • Unlimited deployments
    • Custom serverless compute pricing
    • Cost tracking and insights
    • Personalized onboarding support
    • +8 more
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
Apache Spark
Dagster
CLI
Apache Spark
Dagster
Deployment
Cloud / SaaS
Apache Spark
Dagster
Self-hosted
Apache Spark
Dagster
On-premise
Apache Spark
Dagster
Hybrid
Apache Spark
Dagster

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

Apache Spark

5 total
  • Hadoop
  • HDFS
  • YARN
  • Kubernetes
  • Docker
Independently observed

Dagster

Leader
14 total
  • dbt
  • Snowflake
  • Spark
  • Databricks
  • Azure
  • AWS
  • Airbyte
  • Tableau
  • Soda
  • Slack
  • Microsoft Teams
  • PagerDuty
  • Datadog
  • Python
Independently observed

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.