Siddhi
Siddhi: A flexible choice for teams building event patterns across many data sources. Ranked #16 of 25 in Stream Processing Software by our editors (7.8/10); pricing: Open source; best for teams needing event patterns and many adapters.
At a glance
- Editor score7.8 / 10
- PricingOpen source
- Best forTeams needing event patterns and many adapters
- Paid fromFree
- Deployment modelSelf-hosted
- Facts checked21 Sep 2026
Where it wins
- Streaming SQL with windows, joins, aggregations, and event patterns
- 16 connectors spanning messaging, databases, services, files, and cloud storage
- Embeddable Java and Python libraries with Docker and Kubernetes options
Where it doesn't
- Self-hosted deployment requires teams to manage the operating environment
- Its broad feature set may require specialist streaming knowledge
- Future releases are planned as part of WSO2 Enterprise Integrator
Our verdict on Siddhi
Siddhi is an open-source stream-processing and complex-event-processing platform from WSO2. It is designed for teams building event-driven applications, streaming data integrations, real-time analytics, notifications, and adaptive decision-making. Siddhi Streaming SQL handles filters, windows, joins, aggregations, patterns, and rules, while deployment options include embedded Java or Python libraries, local or Docker microservices, and Kubernetes. It is a strong fit for teams that need event patterns and many adapters rather than a narrow single-purpose stream processor.
The core feature set covers several kinds of streaming state and timing. Time, length, session, batch, and event-time windows support different processing models, while stateful joins, tables, named windows, and aggregations support more involved event logic. Event pattern and sequence processing add a way to express relationships across events. Teams can edit queries graphically or through source and use event simulation during development. Online and pre-trained machine-learning model support extends the platform beyond fixed rules, although the published details do not define the scope of those model workflows.
Siddhi’s ecosystem fit is a central strength. Its 16 connectors include NATS, Kafka, RabbitMQ, HTTP, gRPC, TCP, JMS, IBM MQ, MQTT, Amazon SQS, Google Pub/Sub, Email, WebSocket, File, and Change Data Capture. That range suits environments where events arrive through mixed messaging systems, services, databases, files, and cloud storage. The trade-off is operational ownership: Siddhi is positioned for self-hosted deployment, so platform teams need to manage its runtime and deployment choices. Choose it when flexible event logic, embedding, and connector breadth matter; consider an alternative when a fully managed service is the priority.
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Siddhi pricing
Siddhi fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Deployment model | Self-hosted |
| SQL processing | Yes |
| Stateful processing | Yes |
| Event-time windows | Yes |
| Supported languages | Siddhi Streaming SQL, Java, Python, JavaScript |
| Source connectors | 16 |
| Deployment | Self-hosted, Cloud |
| Platforms | Linux, macOS |
| Support | Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 18 integrations: NATS, Kafka, RabbitMQ, HTTP, gRPC, TCP … See all → |
| Pricing | Open source |
| Website | siddhi.io |
| Facts checked | 21 Sep 2026 |
Siddhi integrations
Siddhi lists 18 integrations on its own site.
- NATS
- Kafka
- RabbitMQ
- HTTP
- gRPC
- TCP
- JMS
- IBM MQ
- MQTT
- Amazon SQS
- Google Pub/Sub
- WebSocket
- File
- Change Data Capture
- Amazon S3
- Google Cloud Storage
- in-memory
Alternatives to Siddhi
- 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
Also Ranked In
Siddhi is ranked in 2 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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