Amazon Kinesis vs Apache Beam

Struggling to choose between Amazon Kinesis and Apache Beam? Both products offer unique advantages, making it a tough decision.

Amazon Kinesis is a Ai Tools & Services solution with tags like realtime, ingestion, processing.

It boasts features such as Real-time data streaming, Scalable data ingestion, Data processing through Kinesis Data Analytics, Integration with other AWS services, Serverless management, Data replay capability and pros including Handles massive streams of data in real-time, Fully managed service, no servers to provision, Automatic scaling to match data flow, Integrates nicely with other AWS services, Replay capability enables reprocessing of data.

On the other hand, Apache Beam is a Development product tagged with batch-processing, streaming, pipelines, java, python.

Its standout features include Unified batch and streaming programming model, Portable across execution engines, SDKs for Java and Python, Stateful processing, Windowing, Event time and watermarks, Side inputs, and it shines with pros like Unified API for batch and streaming, Runs on multiple execution engines, Active open source community, Integrates with other Apache projects.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Amazon Kinesis

Amazon Kinesis

Amazon Kinesis is a managed service that allows for real-time streaming data ingestion and processing. It can ingest data streams from multiple sources, process the data, and route the results to various endpoints.

Categories:
Ai Tools & Services Data Streaming
realtime ingestion processing

Amazon Kinesis Features

  1. Real-time data streaming
  2. Scalable data ingestion
  3. Data processing through Kinesis Data Analytics
  4. Integration with other AWS services
  5. Serverless management
  6. Data replay capability

Pricing

  • Pay-As-You-Go

Pros

Handles massive streams of data in real-time

Fully managed service, no servers to provision

Automatic scaling to match data flow

Integrates nicely with other AWS services

Replay capability enables reprocessing of data

Cons

Can get expensive with high data volumes

Complex to set up and manage

Limits on maximum stream size and shard throughput

No automatic data retention policies

Apache Beam

Apache Beam

Apache Beam is an open source, unified model for defining both batch and streaming data processing pipelines. It provides a simple, Java/Python SDK for building pipelines that can run on multiple execution engines like Apache Spark and Google Cloud Dataflow.

Categories:
Development Data Processing
batch-processing streaming pipelines java python

Apache Beam Features

  1. Unified batch and streaming programming model
  2. Portable across execution engines
  3. SDKs for Java and Python
  4. Stateful processing
  5. Windowing
  6. Event time and watermarks
  7. Side inputs

Pricing

  • Open Source

Pros

Unified API for batch and streaming

Runs on multiple execution engines

Active open source community

Integrates with other Apache projects

Cons

Steep learning curve

Complex dependency management

Not as fast as native engines in some cases