Esper
Esper: A mature, self-hosted choice for Java and C# teams building event-driven applications. Ranked #22 of 25 in Stream Processing Software by our editors (7.2/10); pricing: Free plan; best for java or C# teams using event-processing SQL.
At a glance
- Editor score7.2 / 10
- PricingFree plan
- Best forJava or C# teams using event-processing SQL
- Free planYes
- Paid fromFree
- Deployment modelSelf-hosted
- Founded2006 · Wayne, New Jersey, USA
- Facts checked21 Sep 2026
Where it wins
- SQL-oriented EPL supports filtering, joins, grouping, and aggregations
- Pattern matching, windows, event-time processing, and stateful tables
- Open-source engine with Kafka, JMS, AMQP, HTTP, JDBC, and file adapters
Where it doesn't
- Self-hosted deployment requires teams to manage the runtime
- Commercial licensing and enterprise add-ons require vendor contact
- Narrower coverage than platforms designed for broader streaming use cases
Our verdict on Esper
Esper is an open-source event processing engine for Java and .NET applications. It is designed for developers building complex event processing, streaming analytics, monitoring, fraud detection, and other event-driven applications. The embeddable runtime uses the Event Processing Language (EPL), which provides SQL-standard constructs for continuous queries over event streams. Java and C# teams that want event-processing SQL, rather than a standalone server, are the clearest fit.
Its standout capability is the breadth of stateful stream analysis in one engine. EPL supports filtering, joins, grouping, aggregations, and pattern matching for event sequences. Developers can work with sliding, tumbling, length, and externally timed windows, along with event-time and timestamp-based processing. Named windows and stateful tables support retained application state, while EsperIO adapters connect workflows with File and CSV, JMS, AMQP, Kafka, HTTP, and JDBC systems.
Esper is also a focused option rather than a broad managed streaming platform. It runs self-hosted as an embeddable runtime, so teams need an application architecture that accommodates deployment and operation of the engine. The project has been open source since its founding in 2006, and GPLv2 source distributions are published. Commercial licensing and enterprise add-ons require contacting EsperTech Inc. Choose Esper when SQL-style event processing, temporal windows, pattern detection, and stateful analysis are central requirements. Teams seeking a managed service or wider platform coverage should consider alternatives.
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Esper pricing
Esper 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, C# |
| Source connectors | Not verified |
| Deployment | Self-hosted |
| Support | Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: File and CSV, JMS, AMQP, Kafka, HTTP, JDBC |
| Pricing | Free plan |
| Website | espertech.com |
| Facts checked | 21 Sep 2026 |
Esper integrations
Esper lists 6 integrations on its own site.
- File and CSV
- JMS
- AMQP
- Kafka
- HTTP
- JDBC
Alternatives to Esper
- 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
Esper is ranked in 2 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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