Apache NiFi, Apache Airflow and Airbyte are all open source, but they solve different problems. NiFi routes and transforms streaming data flows through a visual canvas. Airflow schedules and orchestrates tasks you write in Python. Airbyte replicates data from 700+ sources into warehouses, lakehouses and databases with maintained connectors. Here's how to tell which one, or which combination, fits your pipeline.
Apache NiFi vs Airflow vs Airbyte at a glance
| Apache NiFi | Apache Airflow | Airbyte |
|---|
| Category | Visual data flow and routing | Workflow orchestration | Data movement (ELT and CDC) |
| Core job | Move, route and transform data in real time, record by record | Schedule, chain and monitor batch tasks | Extract and load data from 700+ sources on a schedule or via CDC |
| How you build | Drag-and-drop processors on a canvas | Python DAGs | Configure in UI, API, Terraform or PyAirbyte |
| Connectivity | Hundreds of processors for protocols, files, queues and databases | Provider operators and hooks; extract logic is yours to write | 700+ maintained connectors, plus a no-code Connector Builder |
| Processing model | Continuous streaming, with back pressure and prioritization | Batch, scheduled or event-triggered | Batch and incremental syncs, plus CDC |
| Custom extensions | Custom processors in Java, or Python processors in NiFi 2.x | Custom operators in Python | Connector Builder with AI assist, low-code and Python CDKs |
| Data lineage | Built-in record-level provenance | Task-level logs and OpenLineage | Sync logs and job history |
| Pricing | Free (Apache 2.0); you run the cluster | Free (Apache 2.0); you run it, or use a managed provider | Free (Core); Cloud from $20/month; capacity-based on Pro and Enterprise Flex |
| Managed options | Cloudera DataFlow; Snowflake Openflow (built on NiFi) | Astronomer, Amazon MWAA, Google Cloud Composer | Airbyte Cloud, hybrid or Enterprise Flex |
| Current version | NiFi 2.x (2.9.0, April 2026) | Airflow 3.x | Continuous releases |
| Open source | Yes | Yes | Yes |
About Apache NiFi
Apache NiFi is an open-source data flow tool, originally built at the NSA and donated to the Apache Software Foundation in 2014. You design flows on a drag-and-drop canvas, connecting processors that ingest, route, transform and deliver data continuously, with record-level provenance. NiFi 2.0 moved to Java 21 and added Python processors, and the 2.x line now ships new releases every few months. Snowflake Openflow, Snowflake's managed integration service, is built on NiFi.
About Apache Airflow
Apache Airflow is an open-source workflow orchestrator, originally built at Airbnb and now an Apache Software Foundation project. You define workflows as Python DAGs, and Airflow schedules, runs and monitors each task. Airflow 3 is the current major line; Airflow 2 reached end of life on April 22, 2026.
About Airbyte
Airbyte is the open standard for data movement, used by 18% of the Fortune 500. It replicates data from 700+ sources into warehouses, lakehouses, databases and AI context stores, and runs self-hosted, fully managed, or hybrid inside your own boundary.
Three different jobs
All three are open source, but they sit in different parts of a data stack:
- NiFi routes data in motion. It's built for continuous, record-by-record flows from devices, logs, queues and files, with back pressure and prioritization.
- Airflow orchestrates. It decides when each step runs and in what order, but every task is code you write or a tool you call.
- Airbyte replicates data. It syncs SaaS apps, APIs and databases into analytical destinations with incremental loads, CDC and schema handling built in.
Cost: free software, different operating burdens
All three are free to download, so the real cost is running them.
NiFi runs as a stateful Java cluster with content, flowfile and provenance repositories to size and tune. Teams that want it managed typically buy Cloudera DataFlow or use Snowflake Openflow.
Airflow needs schedulers, workers and a metadata database, plus upgrades such as the move from Airflow 2 to 3. Astronomer, Amazon MWAA and Google Cloud Composer run it for a fee.
Airbyte Core is free to self-host. Cloud starts at $20/month (Standard) and $189/month (Plus). Pro and Enterprise Flex price on Data Workers, dedicated compute capacity, so cost doesn't track row counts.
Connectivity
NiFi ships hundreds of processors for protocols, files, message queues and databases, and you can write custom processors in Java or Python. For a SaaS API, you still assemble the flow yourself: authentication, pagination, incremental state and schema mapping.
Airflow's provider packages give you operators and hooks, but a hook is a client, not a pipeline. Extraction logic for each source is code your team maintains.
Airbyte ships 700+ maintained connectors with that logic built in, and its Connector Builder generates new ones from API docs with AI assist.
Streaming vs. batch
NiFi is built for data in motion. It processes records continuously, applies back pressure when downstream systems slow down, and lets you prioritize queues, which suits IoT, logs and edge collection.
Airflow is built for batch: scheduled or event-triggered runs of interdependent tasks.
Airbyte runs scheduled and incremental syncs, plus log-based CDC from production databases, which covers most analytics and AI ingestion without a streaming cluster.
Deployment
NiFi and Airflow both run anywhere you can run Java or Python, from Kubernetes to on-prem servers, and both have managed options.
Airbyte runs four ways on one codebase: free self-hosted Core, managed cloud, hybrid, or fully on-prem with Enterprise Flex.
When to choose NiFi, Airflow or Airbyte
| Your situation | Better fit |
|---|
| You collect continuous data from devices, logs or message queues and need routing and back pressure | Apache NiFi |
| You need record-level provenance for every piece of data in a flow | Apache NiFi |
| You orchestrate multi-step batch workflows across many tools | Airflow |
| You need dependency management, retries and scheduling in Python | Airflow |
| You need SaaS, API or database data in a warehouse without building flows or DAGs | Airbyte |
| You need CDC from production databases with minimal setup | Airbyte |
| You want published pricing and a managed option without a large ops team | Airbyte |
Using them together
These tools often run side by side. NiFi handles real-time edge and log data, Airbyte syncs SaaS and database sources into the warehouse, and Airflow orchestrates the batch steps that follow, including dbt. The official Airbyte provider lets an Airflow DAG trigger a sync and wait for it to finish.
Related comparisons: Airbyte vs Airflow, AWS Glue vs Airflow vs Airbyte, Matillion vs Airflow, Talend vs Airflow.
Build with Airbyte
Ship pipelines in minutes, not sprints. Try Airbyte free or talk to sales.
