Struggling to choose between Apache Beam and Amazon Kinesis? Both products offer unique advantages, making it a tough decision.
Apache Beam is a Development solution with tags like batch-processing, streaming, pipelines, java, python.
It boasts features such as 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 pros including Unified API for batch and streaming, Runs on multiple execution engines, Active open source community, Integrates with other Apache projects.
On the other hand, Amazon Kinesis is a Ai Tools & Services product tagged with realtime, ingestion, processing.
Its standout features include Real-time data streaming, Scalable data ingestion, Data processing through Kinesis Data Analytics, Integration with other AWS services, Serverless management, Data replay capability, and it shines with pros like 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.
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.
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.
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.