What is Samza?
It allows you to build stateful applications that process data in real-time from multiple sources including Apache Kafka.
Samza is a tool in the Message Queue category of a tech stack.
Samza is an open source tool with 604 GitHub stars and 255 GitHub forks. Here’s a link to Samza's open source repository on GitHub
Who uses Samza?
4 companies reportedly use Samza in their tech stacks, including Business, Forensiq, and Metamarkets.
Why developers like Samza?
Here’s a list of reasons why companies and developers use Samza
Be the first to leave a pro
See all jobs
Jobs that mention Samza as a desired skillset
- HIGH PERFORMANCE
- HORIZONTALLY SCALABLE
- EASY TO OPERATE
- WRITE ONCE, RUN ANYWHERE
- PLUGGABLE ARCHITECTURE
Samza Alternatives & Comparisons
What are some alternatives to Samza?
See all alternatives
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
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.
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.