Overview
Apache Flink is a streaming-first framework for continuous data and bounded batch processing. It combines high throughput and low latency with event time, out-of-order events, flexible windows, exactly-once fault tolerance, and back-pressure for long-running stateful data pipelines.
Features and best fit
Based on official documentation; not hands-on tested · Content checked:
Handle event time, windows, and exactly-once processing across streams and batches
The official README lists streaming and batch programs, Java APIs, high throughput with low latency, event-time and out-of-order processing in the DataStream API, and time, count, session, and custom-trigger windows. It also highlights exactly-once fault tolerance, natural back-pressure, and memory management spanning in-memory and out-of-core algorithms.
Sources: [1]
For processing continuous events and historical data in one dataflow model
It fits data platforms combining event ingestion, real-time aggregation, stateful rules, ETL, and bounded replay on a common runtime. With connectors such as Kafka, validate event-time semantics, state size, latency, throughput, and recovery objectives against representative data.
Sources: [1]
Verify externalized connectors, state compatibility, and checkpoint operations per version
The README says many connectors have moved into separate Apache repositories. Test compatibility among core and connector versions, Java, Scala, and Maven, along with state schemas, checkpoints, savepoints, resources, and back-pressure before upgrades. Source builds use Java-specific Maven-wrapper commands. The project is Apache-2.0.
Official sources
- [1]Apache Flink README(2026-09-13)
- [2]Apache Flink LICENSE(2026-09-13)
Supplemental curator note
Selected for qualifying the ambiguous Flink name with Apache, big-data, Java, and SQL vocabulary that leads into stream-processing tasks.
Growth
Growth trends · Last 30 days
26,336 Stars
Trend data is still being collected.
Development activity
Last 90 days · weekly
- Commits (last 30 days)
- 140
- Open PRs
- 367
Development activity is still being collected.
Built with
Categories and tags
Categories
GitHub data
GitHub dataView detailed GitHub data
GitHub Topics
- scala
- java
- big-data
- flink
- python
- sql
- Stars
- 26,336
- Forks
- 14,027
- Watchers
- 901
- Open issues
- 0
- Primary language
- Java
- License
- Apache-2.0
- Repository last updated
- Sep 11, 2026
Explore next
- scikit-learn67,238 Stars
A Python ML library unifying preprocessing, classification, regression, clustering, model selection, and evaluation.
Python - pandas49,724 Stars
A Python DataFrame library for missing values, joins, aggregation, reshaping, time series, and tabular I/O.
Python - Apache Airflow46,842 Stars
A platform for defining DAGs in Python and scheduling, running, and monitoring batch, data, and ML workflows.
Python - Apache Spark43,989 Stars
A large-scale data-processing engine unifying SQL, DataFrames, batch, streaming, and machine learning.
Scala - Apache Kafka33,715 Stars
A distributed event-streaming platform for data pipelines, streaming analytics, and system integration.
Java
Report incorrect information
Tell us if any listing information is incorrect or outdated.