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🔧 Apache Flink

Apache Flink

Stateful Computations over Data Streams.

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Overview

Apache Flink is an open-source, unified stream-processing and batch-processing framework. It is designed to process data in a truly streaming fashion, providing low-latency, high-throughput, and fault-tolerant data processing. Flink's core is a distributed streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.

✨ Key Features

  • True stream processing
  • Stateful and fault-tolerant
  • Low latency and high throughput
  • Event time and processing time semantics
  • Exactly-once processing guarantees
  • Unified API for batch and stream processing

🎯 Key Differentiators

  • True stream processing engine
  • Advanced state management and fault tolerance
  • Low latency

Unique Value: Apache Flink provides a powerful and robust framework for building sophisticated, stateful stream processing applications.

🎯 Use Cases (5)

Real-time data processing Event-driven applications Streaming ETL Complex event processing (CEP) Machine learning on streams

✅ Best For

  • Stream processing at Netflix
  • Real-time analytics at Uber
  • Fraud detection at Alibaba

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Ad-hoc interactive queries
  • Data warehousing

🏆 Alternatives

Apache Spark Streaming Kafka Streams Google Cloud Dataflow

Flink's true streaming architecture and advanced features for state management and event time processing provide lower latency and more accurate results for many streaming use cases compared to micro-batching frameworks.

💻 Platforms

Linux macOS Windows Docker Kubernetes YARN

🔌 Integrations

Apache Kafka Amazon Kinesis RabbitMQ HDFS S3 Elasticsearch

💰 Pricing

Contact for pricing
Free Tier Available

Free tier: Apache Flink is open-source and free to use.

📊 Market Info

Customers: NA

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