Apache Samza
Apache Samza: A free, Kafka-centered stream processor for Java and Scala teams building stateful pipelines. Ranked #13 of 25 in Stream Processing Software by our editors (7.9/10); pricing: Free plan; best for java teams using Kafka-centered stream processing.
At a glance
- Editor score7.9 / 10
- PricingFree plan
- Best forJava teams using Kafka-centered stream processing
- Free planYes
- Paid fromFree
- Deployment modelSelf-hosted
- Founded2013
- Facts checked21 Sep 2026
Where it wins
- High- and low-level APIs plus SQL support different processing styles
- Fault-tolerant state stores support stateful stream processing
- Integrates with Kafka, HDFS, Kinesis, and Azure Event Hubs
Where it doesn't
- Supported languages are limited to Java and Scala
- Connector coverage is narrower than broader stream-processing platforms
- Self-hosted deployment requires teams to manage the runtime environment
Our verdict on Apache Samza
Apache Samza is an open-source distributed framework for applications that consume, transform, and analyze streaming data in real time. It is designed for engineering teams building scalable data pipelines and real-time applications, particularly where Kafka, Hadoop, Amazon Kinesis Data Streams, or Azure Event Hubs are already part of the environment. The framework supports both Java and Scala, with a free deployment model through APIs and self-hosted infrastructure.
Its processing model covers both common stream transformations and more specialized workloads. The high-level Streams API includes filtering, mapping, joins, and windows, while the low-level task API supports per-message processing. SQL-based stream-processing queries provide another entry point. For stateful applications, Samza includes fault-tolerant local state stores and incremental checkpointing. Processing-time tumbling and session windows are available, while event-time processing is provided through Apache Beam integration. Deployment can use Apache YARN with resource management and failure recovery, or a standalone embedded mode with pluggable cluster managers.
Samza fits teams that want Kafka-centered stream processing with Hadoop-oriented infrastructure and control over deployment. Its built-in integrations include Apache Kafka, HDFS, Amazon Kinesis Data Streams, and Azure Event Hubs, with additional integrations for Elasticsearch and Apache Hadoop. The trade-off is a narrower connector and language footprint: the published category specifications list four source connectors and support for Java and Scala. Teams that value these APIs, state stores, windows, and self-hosted control should consider Apache Samza; teams needing broader language or connector coverage should choose a wider platform.
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Apache Samza pricing
Apache Samza fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment model | Self-hosted |
| SQL processing | Yes |
| Stateful processing | Yes |
| Event-time windows | Yes |
| Supported languages | Java, Scala |
| Source connectors | 4 |
| Deployment | Self-hosted |
| Support | Community, Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: Apache Kafka, HDFS, Amazon Kinesis Data Streams, Azure Event Hubs, Elasticsearch, Apache Hadoop |
| Pricing | Free plan |
| Website | samza.apache.org |
| Facts checked | 21 Sep 2026 |
Apache Samza integrations
Apache Samza lists 6 integrations on its own site.
- Apache Kafka
- HDFS
- Amazon Kinesis Data Streams
- Azure Event Hubs
- Elasticsearch
- Apache Hadoop
Alternatives to Apache Samza
- Amazon Managed Service for Apache FlinkA managed Flink service for AWS teams building stateful real-time data pipelines.9.3
- Apache FlinkA free, self-hosted engine for complex stateful stream-processing workloads.9.2
- Azure Stream AnalyticsA strong Azure-native choice for SQL-based, stateful stream processing.9.1
See all Apache Samza alternatives →
Also Ranked In
Apache Samza is ranked in 4 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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