Apache Airflow vs dlt
On the evidence we track, Apache Airflow leads this comparison with a composite score of 73/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Apache Airflow
LeaderA community-built orchestration system that enables users to define data pipelines and tasks in Python, execute them on distributed workers, and monitor progress through a web-based interface. It supports dynamic pipeline generation, extensive third-party integrations, and operates best for batch-oriented workflows.
dlt
A hosted service combining the open-source dlt Python library with managed infrastructure, observability, data quality testing, and team collaboration features for building and running data pipelines.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Apache Airflow
LeaderFree, open-source project. Managed cloud versions available through third parties.
dlt
From $1,190/month with 500 included credits. Free open-source tier. 14-day free trial with $30 credits.
- dltFree
- Apache 2.0 open-source license
- Code-first ingestion library
- Reliable ingestion and loading
- Limited verified OSS connectors
- AI help and community support
- +2 more
- dltHub$1,190/month base + $0.80–$1.00/credit for usage beyond 500 credits/month. 5% discount on annual commitment.
- Everything in dlt, plus:
- Managed runtime
- Hosted Marimo notebooks
- AI Workbench (Claude Code, Codex, Cursor)
- Data quality metrics and checks
- +6 more
- EnterpriseContact sales
- Custom credits and volume pricing
- Enterprise security and governance controls
- Role-based access control (RBAC) and audit logs
- SLA and tailored support options
- Custom onboarding and architecture guidance
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- Microsoft Azure
- Databricks
- Snowflake
- Salesforce
- PostgreSQL
- MySQL
- OpenAI
- SQLite
Apache Airflow
Leader- Amazon Web Services
- Google Cloud Platform
- dbt Cloud
- Slack
- Tableau
- MongoDB
- Redis
- Kubernetes
- Docker
- Apache Spark
- Apache Kafka
- Apache Cassandra
- Apache Flink
- Apache Druid
- Elasticsearch
- Datadog
- Jenkins
- GitHub
- Anthropic
- Cohere
- Pinecone
- Weaviate
- Qdrant
- Oracle
- +18 more
dlt
- HubSpot
- BigQuery
- MotherDuck
- DuckDB
- Amazon S3
- Google Cloud Storage
- SFTP
- Parquet
- Apache Delta
- Apache Iceberg
- DuckLake
- Pydantic Logfire
- Arize
- Langfuse
- LangChain
- Apache Airflow
- Dagster
- AWS Lambda
- Marimo
- Hugging Face
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.