Compare - Beam VS Apache Storm
Here’s the difference between Beam and Apache Storm. The comparison is based on pricing, deployment, business model, and other important factors.
About Beam
Apache Beam is an open source, unified model for defining both batch and streaming data-parallel processing pipelines. Using one of the open source Beam SDKs, you build a program that defines the pipeline. The pipeline is then executed by one of Beam’s supported distributed processing back-ends, which include Apache Flink, Apache Spark, and Google Cloud Dataflow.
About Apache Storm
Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Streaming |
| Stage | Mid Stage | Late Stage |
| Target Segment | Enterprise, Mid size | |
| Deployment | SaaS | |
| Business Model | null | Open Source |
| Pricing | Freemium | |
| Location | null | US |
| Companies using it |   | |
| Contact info |
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