Apache Flink CDC
Apache Flink CDC: A flexible CDC foundation for teams building Flink-based streaming pipelines. Ranked #2 of 22 in Change Data Capture Software by our editors (9.2/10); pricing: Open source; best for flink-based streaming CDC pipelines.
At a glance
- Editor score9.2 / 10
- PricingOpen source
- Best forFlink-based streaming CDC pipelines
- Paid fromFree
- Deployment modelSelf-hosted
- Facts checked20 Sep 2026
Where it wins
- Supports snapshots, incremental reads, and ongoing change-log capture
- Provides exactly-once processing, transformations, routing, and schema evolution
- Connects with databases, Kafka, Iceberg, Hudi, Elasticsearch, and more
Where it doesn't
- Deployment is self-hosted rather than managed
- Requires an Apache Flink-based streaming environment
- Its API choices may add design decisions for smaller CDC projects
Our verdict on Apache Flink CDC
Apache Flink CDC is an open-source change data capture and streaming data integration tool built on Apache Flink. It is aimed at data engineers and organizations creating real-time pipelines, database replication workflows, and streaming ETL jobs. The project captures database changes and synchronizes them with downstream systems through source and pipeline connectors. Teams can define pipelines with YAML or work through DataStream, Table, and SQL APIs.
Its main strength is the combination of initial and ongoing capture. Apache Flink CDC supports database snapshots, incremental snapshot reading, and change-log processing, including exactly-once processing. Schema evolution handles upstream DDL changes, while transformations, table routing, and full database synchronization support more involved replication designs. The connector set covers MySQL, Oracle, PostgreSQL, SQL Server, MongoDB, Db2, TiDB, and Vitess, along with destinations and ecosystem components such as Apache Doris, Elasticsearch, Fluss, Hudi, Iceberg, Kafka, and MaxCompute.
The trade-off is the deployment model: Apache Flink CDC is self-hosted and built around Apache Flink, so it fits teams that want control over a Flink-based CDC stack rather than a turnkey hosted service. Its open-source model suits organizations that can select and operate their own pipeline architecture. Choose it when exactly-once processing, schema evolution, full synchronization, and multiple API styles matter. An alternative may be more suitable for teams seeking a managed CDC product or a narrower setup with fewer platform decisions.
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Apache Flink CDC pricing
Apache Flink CDC fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Deployment model | Self-hosted |
| Capture method | Log-based |
| Source connectors | Not verified |
| Destination connectors | Not verified |
| Schema evolution | Yes |
| Initial snapshot | Yes |
| Deployment | Self-hosted |
| Support | Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 18 integrations: MySQL, Oracle, PostgreSQL, SQL Server, MongoDB, Db2 … |
| Pricing | Open source |
| Website | github.com |
| Facts checked | 20 Sep 2026 |
Apache Flink CDC integrations
Apache Flink CDC lists 18 integrations on its own site.
- MySQL
- Oracle
- PostgreSQL
- SQL Server
- MongoDB
- Db2
- TiDB
- Vitess
- Apache Doris
- Elasticsearch
- Fluss
- Hudi
- Iceberg
- Kafka
- MaxCompute
- OceanBase
- Paimon
- StarRocks
Alternatives to Apache Flink CDC
- DebeziumA flexible, self-hosted CDC platform for streaming database changes across broad ecosystems.9.4
- Oracle GoldenGateA deep enterprise CDC platform for bidirectional replication, migrations, and multicloud data movement.9.0
- EstuaryManaged CDC with exactly-once delivery, flexible destinations, and hybrid deployment.8.8
See all Apache Flink CDC alternatives →
Apache Flink CDC vs the competition
- Apache Flink CDC vs Debezium
- Apache Flink CDC vs Oracle GoldenGate
- Apache Flink CDC vs Estuary
- Apache Flink CDC vs Striim
- Apache Flink CDC vs Google Cloud Datastream
- Apache Flink CDC vs Precisely Connect
Compare Apache Flink CDC with any tool side by side →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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