Apache Flink vs Apache Storm

Apache Flink — Apache Flink is an open-source stream processing framework that performs stateful computations over unbounded and bounded data streams. It offers high throughput, low latency, accurate results, and fa

Apache Storm — Apache Storm is an open source distributed realtime computation system. It processes unbounded streams of data, doing realtime analytics, machine learning, etc. Storm is fault-tolerant and guarantees

Apache Flink offers Distributed stream data processing, Event time and out-of-order stream processing, Fault tolerance with checkpointing and exactly-once semantics, High throughput and low latency, SQL support, while Apache Storm provides Distributed and fault-tolerant, Processes unbounded streams of data, Real-time analytics and machine learning, Processes data rapidly, Integrates with queueing and database technologies.

Apache Flink stands out for High performance and scalability, Flexible deployment options, Fault tolerance; Apache Storm is known for Highly scalable, Fast processing of streaming data, Fault tolerance avoids data loss.

Feature	Apache Flink	Apache Storm
Overall Score	N/A	N/A
Primary Category	Development	Ai Tools & Services
Pricing	Free	Free

Product Overview

Apache Flink

Description: Apache Flink is an open-source stream processing framework that performs stateful computations over unbounded and bounded data streams. It offers high throughput, low latency, accurate results, and fault tolerance.

Apache Storm

Description: Apache Storm is an open source distributed realtime computation system. It processes unbounded streams of data, doing realtime analytics, machine learning, etc. Storm is fault-tolerant and guarantees your data will be processed.

Key Features Comparison

Apache Flink Features

• Distributed stream data processing
• Event time and out-of-order stream processing
• Fault tolerance with checkpointing and exactly-once semantics
• High throughput and low latency
• SQL support
• Python, Java, Scala APIs
• Integration with Kubernetes

Apache Storm Features

• Distributed and fault-tolerant
• Processes unbounded streams of data
• Real-time analytics and machine learning
• Processes data rapidly
• Integrates with queueing and database technologies

Pros & Cons Analysis

Apache Flink

Pros

• High performance and scalability
• Flexible deployment options
• Fault tolerance
• Exactly-once event processing semantics
• Rich APIs for Java, Python, SQL
• Can process bounded and unbounded data streams

Cons

• Steep learning curve
• Less out-of-the-box machine learning capabilities than Spark
• Requires more infrastructure management than fully managed services

Apache Storm

Pros

• Highly scalable
• Fast processing of streaming data
• Fault tolerance avoids data loss
• Integrates with many data sources and technologies
• Open source and free

Cons

• Complex to set up and manage
• Requires DevOps skills to operate and tune
• Only guarantees at-least once processing semantics

Pricing Comparison

Apache Flink

• Free

Apache Storm

• Free