Dagster vs Fivetran
Dagster is the stronger choice for teams that need full pipeline orchestration with asset lineage, testing, and multi-tool coordination. Fivetran wins for teams focused on fast, reliable data ingestion from hundreds of sources without engineering overhead.
Dagster4.3Fivetran4.2
Data Pipelines
Quick Comparison
| Feature | Dagster | Fivetran |
|---|---|---|
| Primary Function | Asset-centric data orchestrator managing pipelines, transformations, and ML workflows with built-in lineage and observability | Managed ELT platform automating data ingestion from 700+ connectors into cloud warehouses with automatic schema management |
| Pricing Model | Open-source self-hosted free (Apache-2.0), Solo Plan $10/mo, Starter Plan $100/mo, Starter $1200/mo, Pro and Enterprise Plan contact sales | Free tier (1 user), Standard $45/mo, Premium custom |
| Ease of Setup | Developer-focused setup requiring Python knowledge, pipeline-as-code approach with local development and CI/CD-native workflows | Fully managed SaaS with point-and-click connector configuration, automated schema evolution, and no infrastructure management needed |
| Integration Ecosystem | Native integrations with Snowflake, BigQuery, dbt, Databricks, Spark, and Fivetran itself via Dagster Pipes for external observability | 700+ pre-built fully managed connectors covering SaaS apps, databases, ERPs, files, and event streams with automatic maintenance |
| Security & Compliance | SOC 2 Type II and HIPAA certified, SSO with RBAC and SCIM provisioning, audit logs, multi-tenant isolation | SOC 1 and SOC 2, GDPR, HIPAA BAA, ISO 27001, PCI DSS Level 1, HITRUST certified with hybrid deployment option |
| Deployment Options | Self-hosted on single server or Kubernetes, or managed Dagster Cloud with hybrid bring-your-own-infrastructure patterns | Fully managed SaaS as default, hybrid deployment option for running pipelines in your own secure environment |
Dagster
- Primary Function:
- Asset-centric data orchestrator managing pipelines, transformations, and ML workflows with built-in lineage and observability
- Pricing Model:
- Open-source self-hosted free (Apache-2.0), Solo Plan $10/mo, Starter Plan $100/mo, Starter $1200/mo, Pro and Enterprise Plan contact sales
- Ease of Setup:
- Developer-focused setup requiring Python knowledge, pipeline-as-code approach with local development and CI/CD-native workflows
- Integration Ecosystem:
- Native integrations with Snowflake, BigQuery, dbt, Databricks, Spark, and Fivetran itself via Dagster Pipes for external observability
- Security & Compliance:
- SOC 2 Type II and HIPAA certified, SSO with RBAC and SCIM provisioning, audit logs, multi-tenant isolation
- Deployment Options:
- Self-hosted on single server or Kubernetes, or managed Dagster Cloud with hybrid bring-your-own-infrastructure patterns
Fivetran
- Primary Function:
- Managed ELT platform automating data ingestion from 700+ connectors into cloud warehouses with automatic schema management
- Pricing Model:
- Free tier (1 user), Standard $45/mo, Premium custom
- Ease of Setup:
- Fully managed SaaS with point-and-click connector configuration, automated schema evolution, and no infrastructure management needed
- Integration Ecosystem:
- 700+ pre-built fully managed connectors covering SaaS apps, databases, ERPs, files, and event streams with automatic maintenance
- Security & Compliance:
- SOC 1 and SOC 2, GDPR, HIPAA BAA, ISO 27001, PCI DSS Level 1, HITRUST certified with hybrid deployment option
- Deployment Options:
- Fully managed SaaS as default, hybrid deployment option for running pipelines in your own secure environment
Community & Adoption Signals
| Metric | Dagster | Fivetran |
|---|---|---|
| GitHub stars | 15.4k | — |
| TrustRadius rating | — | 8.4/10 (54 reviews) |
| PyPI weekly downloads | 1.6M | 13.4k |
| Docker Hub pulls | 5.2M | — |
| Search interest | 2 | 2 |
| Product Hunt votes | 302 | 85 |
As of 2026-05-04 — updated weekly.
Interface Preview
Dagster
Feature Comparison
| Feature | Dagster | Fivetran |
|---|---|---|
| Data Movement | ||
| Pre-built Connectors | Integrates with major platforms via native connectors for Snowflake, BigQuery, dbt, Databricks, and Spark | 700+ fully managed connectors for SaaS, databases, ERPs, files, and event streams with automatic maintenance |
| Change Data Capture | Relies on external CDC tools orchestrated through Dagster Pipes with metadata tracking | Built-in log-based CDC replication for efficient, low-impact database syncs |
| Incremental Syncs | Asset partitioning and versioning enable incremental materialization of data assets | Automatic incremental syncs with schema evolution handling and 15-minute or 1-minute sync intervals |
| Orchestration & Workflow | ||
| Pipeline Paradigm | Asset-centric orchestration with declarative workflows modeling data assets, dependencies, and lineage in code | ELT-first automated pipelines focused on extracting and loading data for downstream transformation |
| Transformation Support | Orchestrates dbt, Databricks, Python, and Spark transformations as first-class pipeline components | Built-in dbt integration with Quickstart data models for analytics-ready transformations upon load |
| Scheduling & Triggers | Flexible scheduling with asset sensors, partition-based triggers, and event-driven materialization | Automated sync scheduling with configurable intervals from 1-minute to 15-minute frequencies |
| Observability & Monitoring | ||
| Data Lineage | Built-in lineage graphs showing asset dependencies, ownership, and auto-generated documentation | Connector-level sync monitoring with logs and alerts for sync health and schema changes |
| Alerting & Health Checks | Intelligent alerts via Slack with AI-powered debugging, impact analysis, and real-time health metrics | Reliability and monitoring dashboards with logs and alerts tracking sync health and schema drift |
| Data Catalog | Integrated data catalog with Compass feature turning warehouse data into stakeholder-facing answers | Connector directory with metadata about sources and destinations but no built-in data catalog |
| Developer Experience | ||
| Local Development | Full local development environment with unit testing, branch deployments, and CI/CD-native workflows | SaaS-based configuration through web UI and REST API with no local development environment |
| Extensibility | Python-based SDK with modular, reusable components and Dagster Pipes for external system observability | REST API for programmatic pipeline creation plus Connector SDK for building custom source connectors |
| Testing & CI/CD | Built-in unit testing framework with branch deployments enabling pipeline testing before production | No built-in testing framework; relies on monitoring dashboards to verify sync correctness after deployment |
| Enterprise & Security | ||
| Access Control | SSO with RBAC and SCIM provisioning supporting Google, GitHub, and SAML identity providers | Role-based access control on all tiers, SCIM/user provisioning and custom roles on Enterprise tier |
| Compliance Certifications | SOC 2 Type II and HIPAA certified with audit logs and configurable retention policies | SOC 1, SOC 2, GDPR, HIPAA BAA, ISO 27001, PCI DSS Level 1, and HITRUST certified |
| Deployment Isolation | Multi-tenant code deployments with isolated code and data, flexible cloud region selection | Hybrid deployment running pipelines in your environment with customer-managed encryption keys on Business Critical |
Data Movement
Pre-built Connectors
DagsterIntegrates with major platforms via native connectors for Snowflake, BigQuery, dbt, Databricks, and Spark
Fivetran700+ fully managed connectors for SaaS, databases, ERPs, files, and event streams with automatic maintenance
Change Data Capture
DagsterRelies on external CDC tools orchestrated through Dagster Pipes with metadata tracking
FivetranBuilt-in log-based CDC replication for efficient, low-impact database syncs
Incremental Syncs
DagsterAsset partitioning and versioning enable incremental materialization of data assets
FivetranAutomatic incremental syncs with schema evolution handling and 15-minute or 1-minute sync intervals
Orchestration & Workflow
Pipeline Paradigm
DagsterAsset-centric orchestration with declarative workflows modeling data assets, dependencies, and lineage in code
FivetranELT-first automated pipelines focused on extracting and loading data for downstream transformation
Transformation Support
DagsterOrchestrates dbt, Databricks, Python, and Spark transformations as first-class pipeline components
FivetranBuilt-in dbt integration with Quickstart data models for analytics-ready transformations upon load
Scheduling & Triggers
DagsterFlexible scheduling with asset sensors, partition-based triggers, and event-driven materialization
FivetranAutomated sync scheduling with configurable intervals from 1-minute to 15-minute frequencies
Observability & Monitoring
Data Lineage
DagsterBuilt-in lineage graphs showing asset dependencies, ownership, and auto-generated documentation
FivetranConnector-level sync monitoring with logs and alerts for sync health and schema changes
Alerting & Health Checks
DagsterIntelligent alerts via Slack with AI-powered debugging, impact analysis, and real-time health metrics
FivetranReliability and monitoring dashboards with logs and alerts tracking sync health and schema drift
Data Catalog
DagsterIntegrated data catalog with Compass feature turning warehouse data into stakeholder-facing answers
FivetranConnector directory with metadata about sources and destinations but no built-in data catalog
Developer Experience
Local Development
DagsterFull local development environment with unit testing, branch deployments, and CI/CD-native workflows
FivetranSaaS-based configuration through web UI and REST API with no local development environment
Extensibility
DagsterPython-based SDK with modular, reusable components and Dagster Pipes for external system observability
FivetranREST API for programmatic pipeline creation plus Connector SDK for building custom source connectors
Testing & CI/CD
DagsterBuilt-in unit testing framework with branch deployments enabling pipeline testing before production
FivetranNo built-in testing framework; relies on monitoring dashboards to verify sync correctness after deployment
Enterprise & Security
Access Control
DagsterSSO with RBAC and SCIM provisioning supporting Google, GitHub, and SAML identity providers
FivetranRole-based access control on all tiers, SCIM/user provisioning and custom roles on Enterprise tier
Compliance Certifications
DagsterSOC 2 Type II and HIPAA certified with audit logs and configurable retention policies
FivetranSOC 1, SOC 2, GDPR, HIPAA BAA, ISO 27001, PCI DSS Level 1, and HITRUST certified
Deployment Isolation
DagsterMulti-tenant code deployments with isolated code and data, flexible cloud region selection
FivetranHybrid deployment running pipelines in your environment with customer-managed encryption keys on Business Critical
Our Verdict
Dagster is the stronger choice for teams that need full pipeline orchestration with asset lineage, testing, and multi-tool coordination. Fivetran wins for teams focused on fast, reliable data ingestion from hundreds of sources without engineering overhead.
When to Choose Each
Choose Dagster if:
Choose Dagster if your team needs to orchestrate complex, multi-step data pipelines across dbt, Spark, Databricks, and Python transformations with full asset lineage and observability. Dagster shines when data engineers want code-first workflows with unit testing, branch deployments, and CI/CD integration. Its open-source Apache-2.0 core and $10/mo Solo plan make it cost-effective for smaller teams, while enterprise features like multi-tenant isolation and Compass data catalog serve larger organizations.
Choose Fivetran if:
Choose Fivetran if your primary need is centralizing data from dozens or hundreds of SaaS applications, databases, and ERPs into your cloud warehouse without building custom connectors. Fivetran's 700+ managed connectors with automatic schema evolution and incremental syncs eliminate connector maintenance entirely. Its free tier with 500,000 monthly active rows provides a genuine starting point, and enterprise compliance certifications including PCI DSS Level 1 and HITRUST make it suitable for regulated industries.
This verdict is based on general use cases. Your specific requirements, existing tech stack, and team expertise should guide your final decision.
Frequently Asked Questions
Can Dagster and Fivetran be used together?
Dagster and Fivetran integrate directly and are commonly used together in modern data stacks. Dagster includes a native Fivetran integration that allows you to orchestrate Fivetran syncs as assets within your Dagster pipeline. This means you can trigger Fivetran data ingestion, then run dbt transformations and downstream processing all within a single Dagster-managed workflow with full lineage visibility. Many teams use Fivetran for its 700+ managed connectors to handle data extraction and loading, while Dagster orchestrates the broader pipeline including transformations, quality checks, and ML workflows.
What are the main pricing differences between Dagster and Fivetran?
Dagster offers an open-source self-hosted option under Apache-2.0 that is completely free. Its managed Dagster Cloud starts at $10/mo for the Solo plan with 7,500 credits/month and 1 user, scaling to $100/mo for the Starter plan with 30,000 credits/month and up to 3 users. Fivetran uses usage-based pricing measured in monthly active rows (MAR), starting with a free tier that includes 500,000 MAR and unlimited users. Fivetran's Standard, Enterprise, and Business Critical tiers scale based on data volume. The pricing models differ fundamentally: Dagster charges for compute credits while Fivetran charges for data rows moved.
Which tool is better for teams without dedicated data engineers?
Fivetran is the better choice for teams without dedicated data engineers. Its fully managed SaaS platform requires no infrastructure management, no code to write, and no connectors to maintain. You configure data sources through a point-and-click web interface, and Fivetran handles schema evolution, incremental syncs, and connector updates automatically. Dagster, by contrast, requires Python development skills and infrastructure knowledge. Its pipeline-as-code approach with asset definitions, sensors, and schedules is powerful but assumes engineering expertise. Teams with analysts but no engineers will be productive with Fivetran much faster.
How do Dagster and Fivetran compare on data observability?
Dagster provides deeper data observability through its asset-centric architecture. Every data asset has built-in lineage graphs showing dependencies and downstream impact, health checks tracking freshness and quality, and auto-generated documentation. Dagster's Compass feature turns warehouse data into answers for stakeholders. Dagster also offers AI-powered debugging and impact analysis for alerts. Fivetran provides sync-level observability with monitoring dashboards, logs, and alerts for sync health and schema changes. Fivetran's observability focuses on the ingestion layer, tracking whether data arrived correctly, while Dagster's spans the entire pipeline from ingestion through transformation to consumption.