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Apache Storm vs KSQL: What are the differences?
Apache Storm: Distributed and fault-tolerant realtime computation. Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 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; KSQL: Open Source Streaming SQL for Apache Kafka. KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.
Apache Storm and KSQL can be categorized as "Stream Processing" tools.
Apache Storm and KSQL are both open source tools. Apache Storm with 5.81K GitHub stars and 3.94K forks on GitHub appears to be more popular than KSQL with 2.4K GitHub stars and 498 GitHub forks.
Spotify, Twitter, and Yelp are some of the popular companies that use Apache Storm, whereas KSQL is used by Doodle, Landoop, and FREE NOW (formerly mytaxi). Apache Storm has a broader approval, being mentioned in 57 company stacks & 64 developers stacks; compared to KSQL, which is listed in 3 company stacks and 7 developer stacks.
Pros of Apache Storm
- Flexible10
- Easy setup6
- Event Processing4
- Clojure3
- Real Time2
Pros of KSQL
- Streamprocessing on Kafka3
- SQL syntax with windowing functions over streams2
- Easy transistion for SQL Devs0