Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
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Dagster
✓ verifiedFreemium
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
152K visits/mo
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Defang
✓ verifiedFreemium
Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
20K visits/mo
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Union Cloud
✓ verifiedPaid
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
25K visits/mo
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Releem
✓ verifiedFree trial
Continuously analyzes MySQL, MariaDB, and PostgreSQL workloads to recommend and safely apply configuration and query fixes.
22K visits/mo5.1K saves
Pricing
Solo: $10/mo + $0.040/credit (1 user)
Starter: $100/mo + $0.035/credit (up to 3 users)
Free trial available
Starter: $0 (1 cloud account)
Pro: $49/mo (1 account, +$29/mo per extra)
Enterprise: $499/mo (3 accounts, +$49/mo per extra)
Team: $950/month + usage (1,000 concurrent actions, 30-day retention, 1 cluster)
Starter: $39/month billed annually (1 database server, or $49/month on-demand)
Scale: $123/month billed annually (up to 5 database servers, or $199/month on-demand)
Hosting: $99/month (up to 9 database servers)
Free trial available
Core features
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- ✦One-command deploy from Docker Compose
- ✦Deploys into your own or a customer's cloud account
- ✦Native managed LLM access (Bedrock/Vertex/Azure AI)
- ✦Managed Postgres, MongoDB and Redis
- ✦Auto-configured IAM, VPC, TLS and load balancing
- ✦Open-source CLI and cloud providers
- ✦Python-native dynamic workflow authoring
- ✦Automatic failure recovery, caching, and versioning
- ✦Zero Trust architecture keeping data inside customer's cloud
- ✦Real-time inference and agentic-AI workflow support
- ✦High-throughput scaling (tens of thousands of actions per run)
- ✦Local development environment matching production behavior
- ✦Workload-based configuration tuning
- ✦SQL query analytics and optimization suggestions
- ✦Schema optimization (duplicate/unused index detection)
- ✦24/7 automated health and security monitoring
- ✦One-command agent installation
- ✦Human approval required before applying changes
Use cases
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms
- →Shipping AI agents and web apps to production
- →Deploying the same app across many customer clouds
- →Agencies deploying into client cloud accounts
- →Avoiding hand-written Terraform or Kubernetes
- →ML teams orchestrating training and inference pipelines at scale
- →Biotech/geospatial companies needing GPU-heavy pipeline orchestration
- →Enterprises migrating off Airflow for ML workflow management
- →Teams requiring workflows that never send data outside their own cloud
- →Database teams reducing manual tuning workload
- →Hosting providers optimizing customer databases at scale
- →Engineering teams without a dedicated DBA fixing performance issues
- →AWS RDS users tuning managed database instances
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