What Apache Flink does

Apache Flink is an open-source, distributed processing engine for stateful computations over bounded and unbounded data streams, governed by the Apache Software Foundation (ASF), a 501(c)(3) non-profit incorporated in Delaware, USA. Originating from the Stratosphere research project at the Technical University of Berlin, Flink entered the Apache Incubator in 2014, became an ASF top-level project, and released its first stable version (1.0.0) in March 2016. Flink 2.0.0 in March 2025 marked the first major release in nine years, introducing disaggregated state management and enhanced batch processing. The platform targets enterprise data engineering teams, data platform architects, and verticals such as financial services and IoT/connected industries that require exactly-once state consistency, event-time processing with late data handling, and unified batch/stream APIs.

The core platform consists of a distributed execution engine with layered APIs (SQL, Table API, DataStream API, ProcessFunction) supporting in-memory computation, incremental checkpointing for large state, and deployment across common cluster environments including YARN, Kubernetes, and standalone clusters. The ecosystem extends the core with 30+ first-party connectors (Kafka, Pulsar, Kinesis, Cassandra, Elasticsearch, HBase, Hive, JDBC, MongoDB, RabbitMQ, Prometheus, etc.), Flink CDC for change data capture, Flink Agents for AI/LLM integration, Stateful Functions for serverless event-driven applications, Flink ML for iterative machine learning, a Kubernetes Operator for container orchestration, and Table Store for lakehouse storage. Flink integrates with Apache Iceberg, Delta Lake (via Databricks Unity Catalog), and DuckDB to participate in open lakehouse architectures.

As an open-source framework under the Apache License v2.0, Apache Flink does not generate software licensing revenue; distribution is free via ASF mirrors, Maven Central, GitHub Releases, Docker Hub, and the Kubernetes Operator. Go-to-market is community-led through documentation, mailing lists, Slack, Stack Overflow, community meetups, the Apache Flink blog, and an active PMC. Infrastructure sponsorship is provided in kind by Alibaba, AWS, and Ververica (compute for CI, benchmarks, and connector testing). Commercial monetization of the broader Flink ecosystem accrues to downstream vendors offering managed services and cloud products (e.g., Ververica, AWS Kinesis Data Analytics, Alibaba Realtime Compute for Apache Flink) rather than to the project itself. Trademarks are held by the Apache Software Foundation, and no single commercial entity holds equity in the project.

Name

Apache Flink

Legal name

Apache Flink

Website

https://flink.apache.org

Company type

Private

Founded year

2014

Operating status

Operating

Short description

Apache Flink is an Apache Software Foundation open-source distributed processing engine for stateful stream and batch computations. It serves enterprise data engineering teams, data platform architects, and verticals like financial services and IoT requiring exactly-once guarantees, event-time processing, and unified batch/stream APIs.

Ownership category

akta.pro rank

Product category

Stream Processing Framework

NAICS

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821), Computer Systems Design and Related Services (54151)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming, Data Processing, Etc. (7370)

akta.pro primary industry

Real-Time / Streaming Data Warehousing (HDAEABAF)

Keywords

• Stream processing framework
• Distributed data processing
• Real-time analytics
• Stateful stream processing
• Event-driven applications

Headquarters

HQ city

Wilmington

HQ country

United States

HQ region

North America

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Infrastructure, Operations, Others

Revenue model

1. Open Source Distribution: Apache Flink is freely distributed under the Apache License v2.0. Revenue is not generated directly from the open-source software. Organizations that commercialize Flink-based products or provide managed services around Flink may generate revenue through enterprise support, cloud offerings, or consulting.

Pricing tiers

Go-to-market motion1 record

Distribution channels5 records

Marketing channels8 records

Core offering

Apache Flink is an open-source framework and distributed processing engine for stateful computations over unbounded and bounded data streams. It is designed to run in all common cluster environments, perform computations at in-memory speed, and scale to any workload. The framework exposes layered APIs (SQL, DataStream API, ProcessFunction) and supports event-driven applications, stream and batch analytics, and ETL data pipelines.

Product overview

Apache Flink is an open-source framework and distributed processing engine for stateful computations over unbounded and bounded data streams. The platform follows a modular architecture centered on the Flink Core engine, which provides layered APIs including DataStream API, DataSet API, Table API/SQL, and ProcessFunction for different programming abstractions. The ecosystem extends the core with specialized modules: Flink Connectors (30+ connectors for Kafka, databases, cloud services), CDC for change data capture, Agents for AI/LLM integration, Stateful Functions for serverless applications, ML for machine learning, Kubernetes Operator for container orchestration, and Table Store for lakehouse storage. Flink is designed for high-performance, low-latency stream processing with exactly-once consistency guarantees, event-time processing, and in-memory computation at any scale.

Differentiator

Problem solved

Functional benefit

Products and services

• Apache Flink Core Framework and distributed processing engine for stateful computations over unbounded and bounded data streams, designed for enterprise data engineering teams building event-driven applications, real-time analytics platforms, and ETL data pipelines.
• Apache Flink CDC Change Data Capture framework for real-time data integration from database sources, enabling streaming CDC pipelines from various databases for data engineering and analytics teams.
• Apache Flink Agents AI agent framework for building intelligent applications that combine LLM capabilities with real-time stream processing, targeted at developers building AI-augmented event-driven systems.
• Apache Flink Stateful Functions Framework for building stateful serverless applications and event-driven microservices, providing portable stateful functions deployable on Flink clusters for application developers.
• Apache Flink ML Machine learning library providing algorithms, features, and utilities for building ML pipelines on Flink, supporting iterative ML workflows for data science teams.
• Apache Flink Kubernetes Operator Kubernetes operator for deploying and managing Flink applications on Kubernetes clusters, with Helm chart support for platform and DevOps teams.
• Apache Flink Table Store Open-source table format and storage engine for lakehouse architectures, providing ACID transaction capabilities and time travel queries on cloud object storage for data platform teams.
• Apache Flink Connectors Collection of connectors for integrating Flink with external systems including Kafka, Pulsar, AWS Kinesis, Google Cloud Pub/Sub, RabbitMQ, Cassandra, MongoDB, Elasticsearch, HBase, Hive, JDBC, and Prometheus, used by data engineering teams for data pipeline integration.

Quantifiable outcome

• 73% of enterprises implementing real-time data processing solutions experience a 40% increase in decision-making speed
• +3 more outcomes

Segments4 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration18 records

AI capability4 records

Feature7 records

Partnerships

Five partnerships are on record, tiered minor, core and moderate.

• AlibabaminorOthersAlibaba donated 8 machines (32vCPU, 64GB) to run continuous integration tasks for the Flink repository and Pull Requests on Azure Pipelines.
• AWS (Amazon Web Services)coreTechnology or IntegrationAWS donated AWS service costs for integration testing of the flink-connector-aws project. AWS has also collaborated on DuckDB integration with Iceberg REST catalogs, enabling lightweight analytics on cloud-stored Iceberg tables.
• VervericamoderateOthersVerverica donated one machine (1vCPU, 2GB) for maintaining the flink-ci image repository and one machine (8vCPU, 64GB) for running daily Flink Benchmarks.
• DatabrickscoreTechnology or IntegrationDatabricks Unity Catalog now supports external engines including Apache Flink to create, read, and write to Unity Catalog managed Delta tables, enabling open lakehouse interoperability.
• NetflixminorOthersNetflix originally developed Apache Iceberg and now contributes to the Apache Software Foundation project. Netflix uses Iceberg for analytics and AI/ML workloads alongside Flink.

Scale indicators5 records

Recent moves6 records

Expansion highlights6 records

Broad incumbents

• Confluent: Commercial vendor behind Apache Kafka, offering a complete data-streaming platform including ksqlDB and Kafka Streams. Competes with Flink for end-to-end streaming workloads, particularly where Kafka-centric architectures dominate.
• Google Cloud Dataflow: Google's fully managed stream and batch processing service, implementing the Apache Beam programming model. Competes directly with Flink for managed, cloud-native streaming workloads.
• AWS Kinesis Data Analytics: Managed stream-processing service from AWS, built on Apache Flink. Represents the most direct commercial/cloud-managed alternative to self-hosted Flink and is a core distribution channel for Flink workloads inside AWS.

Direct peers

• Apache Kafka: The de facto distributed event-streaming platform. Often paired with Flink as the messaging backbone, but Kafka Streams also overlaps directly with Flink's stream-processing capabilities for lighter-weight use cases.
• Apache Beam: Open-source unified programming model for batch and streaming data pipelines with execution on runners including Flink, Spark, and Google Cloud Dataflow. Direct functional peer in the unified batch/stream API space.
• Apache Spark: The dominant open-source unified analytics engine for large-scale batch and stream processing. Directly comparable to Flink as the principal open-source alternative for distributed data processing, with Structured Streaming as Flink's primary functional competitor.

Emerging players

• Ververica: Original commercial steward of Apache Flink (founded by Flink's creators) and a current infrastructure sponsor. Provides enterprise/managed Flink offerings (Ververica Platform, VERA), making it the closest commercial pure-play built around Flink.
• Decodable: Cloud-native stream-processing platform built on Apache Flink, founded by Flink's original creators (the team behind Ververica's open-source origins). Competes as a managed-service alternative to self-hosted Flink deployments.
• Materialize: Cloud-native streaming SQL database built on Timely Dataflow, providing real-time materialized views via standard SQL. Competes for the same low-latency, incrementally-maintained-query workloads that Flink SQL targets.
• Apache Pulsar: Open-source distributed messaging and streaming platform with built-in Functions framework for lightweight stream processing. Overlaps with Flink on real-time event processing while serving as a complementary messaging layer.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/apacheflink
• GitHubgithub.com/apache/flink

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Funding overview

Funding rounds

Investors

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M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Apache Flink