Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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Pulumi
✓ verifiedFreemium
Infrastructure-as-code platform to define and manage cloud resources in general-purpose languages, with an AI infra agent for teams.
1.9K saves
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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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CloudKeeper Tuner
✓ verifiedPaid
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
43K visits/mo
Pricing
Individual: $0 forever (1 user, 500 deployment minutes, 5M Neo tokens/mo)
Solo: $10/mo + $0.040/credit (1 user)
Starter: $100/mo + $0.035/credit (up to 3 users)
Free trial available
CloudKeeper Tuner: 2% of monthly AWS bill (1% for CloudKeeper AZ/EDP+ customers)
Free trial available
Core features
- ✦IaC in multiple general-purpose languages
- ✦State management for projects, stacks, and environments
- ✦Neo AI infrastructure agent
- ✦Secrets and configuration management
- ✦Registry of 170+ providers and reusable packages
- ✦Insights, governance, and compliance remediation
- ✦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
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
Use cases
- →Provisioning multi-cloud infrastructure programmatically
- →Managing secrets and environment configuration
- →Building internal developer platforms
- →Automating deployments with CI/CD
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
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