Here’s the difference between Brooklin and Apache Storm. The comparison is based on pricing, deployment, business model, and other important factors.
Brooklin is a distributed system intended for streaming data between various heterogeneous source and destination systems with high reliability and throughput at scale. Designed for multitenancy, Brooklin can power hundreds of simultaneous data pipelines across different systems and can be easily extended to support new sources and destinations.
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.
Overview | ||
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Categories | Data Streaming | Data Streaming |
Stage | undefined | Late Stage |
Target Segment | Enterprise, Mid size | |
Deployment | SaaS | |
Business Model | null | Open Source |
Pricing | Freemium | |
Location | null | US |
Companies using it | ||
Contact info |