Suggestions appear as you type. Use the up and down arrows to choose one and Enter to open it.

This page's audience our own tag's counts — open to see them
–Visits
–Page views
–Clicks to vendors
–Time on page
–Reading now
Clicks to vendors, by tool
  • –
Top countries
  • –
Devices
  • –

– · visits, page views and clicks counted by our own tag, which counts more than our checked analytics; every figure rounded down · how we count

Apache Flink

Apache Flink: A free, self-hosted engine for complex stateful stream-processing workloads. Ranked #2 of 25 in Stream Processing Software by our editors (9.2/10); pricing: Free plan; best for teams needing a full-featured open stream engine.

9.2/10Editor score
Apache Flink9.2 Visit Apache Flink

At a glance

  • Editor score
    9.2 / 10
  • Pricing
    Free plan
  • Best for
    Teams needing a full-featured open stream engine
  • Free plan
    Yes
  • Paid from
    Free
  • Deployment model
    Self-hosted
  • Facts checked
    21 Sep 2026
Apache Flink screenshot
  • Where it wins

    • Stateful processing with event-time windows and late-data handling
    • Exactly-once consistency with checkpoint-based recovery
    • SQL, DataStream API, and broad connector support
  • Where it doesn't

    • Self-hosted operation requires team-managed deployment and infrastructure
    • Deployment options center on standalone, Kubernetes, and YARN
    • DataStream programs are Java-based

Our verdict on Apache Flink

Apache Flink is an open-source distributed processing engine for bounded and unbounded data streams. It is designed for engineering and data-platform teams building event-driven applications, streaming analytics, data pipelines, and ETL workloads. The product combines real-time stream processing with batch processing, supporting keyed state, state backends, event-time semantics, watermarks, late-data handling, windows, joins, aggregations, SQL, and the Table API.

Its strongest technical fit is for workloads where state and processing guarantees matter. Flink provides exactly-once state consistency and checkpoint-based recovery, while time-based windows and sessionization support common streaming transformations. SQL and Table API queries offer a higher-level option for streaming and batch work, and the DataStream API supports Java-based stream programs. The connector ecosystem covers Apache Kafka, Amazon Kinesis Data Streams, Amazon Kinesis Data Firehose, databases, filesystems, cloud services, and systems including MongoDB, Elasticsearch, OpenSearch, Apache Pulsar, RabbitMQ, Google Cloud Pub/Sub, Amazon SQS, and Apache Cassandra.

Flink is distributed as open-source software rather than a vendor-hosted commercial plan, so its value comes from avoiding license costs while retaining control over deployment. Teams can run it locally, as a standalone cluster, or with Kubernetes and YARN, but they are responsible for operating that environment. The platform is a strong choice for organizations that need a broad stream-processing engine with SQL, stateful computation, recovery, and multiple deployment paths. Teams seeking a managed service with vendor-operated infrastructure should consider a different product category or deployment model.

Your product? Our editors can test Apache Flink in depth and publish a review, labelled as paid · from $149/mo →

Apache Flink pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on flink.apache.org

Apache Flink fact sheet

Free planYes
Paid fromFree
Deployment modelSelf-hosted
SQL processingYes
Stateful processingYes
Event-time windowsYes
Supported languagesJava, Python, Scala
Source connectors7
DeploymentSelf-hosted
SupportDocs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations15 integrations: Apache Kafka, Amazon Kinesis Data Streams, Amazon Kinesis Data Firehose, Amazon DynamoDB, JDBC databases, Apache HBase … See all →
PricingFree plan
Websiteflink.apache.org
Facts checked21 Sep 2026

Apache Flink integrations

Apache Flink lists 15 integrations on its own site.

  • Apache Kafka
  • Amazon Kinesis Data Streams
  • Amazon Kinesis Data Firehose
  • Amazon DynamoDB
  • JDBC databases
  • Apache HBase
  • Apache Hive
  • MongoDB
  • Elasticsearch
  • OpenSearch
  • Apache Pulsar
  • RabbitMQ
  • Google Cloud Pub/Sub
  • Amazon SQS
  • Apache Cassandra

See all Apache Flink integrations →

Alternatives to Apache Flink

See all Apache Flink alternatives →

Apache Flink vs the competition

Compare Apache Flink with any tool side by side →

Also Ranked In

Apache Flink is ranked in 5 of our directories.

Used Apache Flink? Be the first to review it

The editor score above is our own research. What this page doesn't have yet is a reader's view — what you used Apache Flink for, what worked and what didn't. No stars are seeded and no review is paid for; an editor reads every one before it appears.

Write a reviewTwo minutes · verified accounts only · read by an editor before it appears

Reviews come only from verified accounts. Sign in or create an account first — your e-mail is never shown.

Your rating

0 characters · at least 80, up to 3,000

Posted from your verified account. Reviews appear after an editor reads them, usually within two working days.

Featured on iTechGuides

Featured on iTechGuides — Apache Flink 9.2/10

Apache Flink is listed in our Stream Processing Software directory. Add the badge to your site — it links back to this page.

<a href="https://www.itechguides.com/products/apache-flink/"><img src="https://www.itechguides.com/best/badge/apache-flink.svg" alt="Featured on iTechGuides" width="230" height="46"></a>

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated · How we research and update