Vendors and Products in the Event Stream Processing Market

8 November 2023   W. Roy Schulte

The proliferation of streaming event data is driving more use of event stream processing (ESP) platforms. ESP platforms provide development-time and run-time facilities that make it easier for developers to build applications that process streaming data “in motion.” They operate on event data as it arrives before (optionally) landing it into a database, file store, or in-memory data grid.

ESP applications generate complex events by performing stateful calculations on moving time windows of event data. Some ESP applications implement stream analytics to update real-time dashboards, send alerts, forward intermediate results (complex events) to other applications, or trigger immediate actions in response to situations that have been detected (i.e., sense-and-respond behavior). Other ESP applications implement stream data integration pipelines to filter, enrich and transform input data and then load the data into data stores for subsequent processing (typically for analytics).

We can sort modern general-purpose ESP platforms into three major categories:

A. Free, community-supported open source
B. Commercial, vendor-supported “open core” products that combine an open-source core with proprietary value-added capabilities
C. Commercial, closed-source products

Vendors also offer a wide variety of purpose-specific, vertically- or horizontally-oriented products that have embedded ESP capabilities. These sometimes embed a general-purpose, open-source ESP platform (see (A) above) but otherwise they develop their own custom-built ESP capabilities. Examples of such purpose-specific streaming products include IoT platforms, stream data integration tools, and applications for supply chain visibility, security information and event management (SIEM), asset performance management, fraud detection, real-time customer relationship management, and other business purposes.

Lists by Category

A. Free, community-supported open source

User organizations choose this kind of ESP platform when they want to avoid paying license fees while leveraging the work of multiple other software developers. Pure open-source products appeal to risk-tolerant buyers who are willing to develop some ancillary utilities and perform manual operations themselves. Apache Flink is the most-widely used open-source offering for new projects. However, many organizations use Apache Spark Streaming, Apache Storm, Esper and other products.

Examples (origin in parenthesis):
1. Apache Flink
2. Apache Samza (LinkedIn)
3. Apache Spark Streaming (Databricks)
4. Apache Storm, Apache Heron (X, formerly Twitter)
5. Drools Fusion (Red Hat)
6. Esper, Neser (EsperTech)
7. Jet (Hazelcast)
8. Kafka ksqlDB, Kafka Streams (Confluent)

B. Commercial, vendor-supported open core products

These products appeal to organizations that want the assurance of support from a vendor and the benefits of added-value, differentiated development and management features on an open-source foundation.

Examples (underlying ESP platform in parenthesis):

1. Alibaba Ververica Platform (Flink)
2. Amazon Kinesis Data Analytics (Flink)
3. Axual KSML (Kafka Streams)
4. Celonis Lenses Streaming SQL (Kafka Streams)

5. Cloudera DataFlow (Flink)

6. Confluent Platform, Confluent Cloud (ksqlDB, Flink)
7. EsperTech Esper Enterprise Edition
8. Google Cloud DataFlow (Beam), Cloud IoT Edge
9. IBM Decision Manager Open Edition (Drools)

10. VMware Tanzu Spring Cloud Data Flow
11. WSO2 Stream Processor (Siddhi)

C. Commercial, closed-source products

Some of the most popular ESP platforms are proprietary, closed-source products. These appeal to buyers who require vendor support and typically are buying lots of other software from the same vendor. Many of these products come from major vendors with vast product lines.

Examples:
1. FASTDATA.io PlasmaENGINE
2. Hitachi Streaming Data Platform
3. Microsoft Azure Stream Analytics, StreamInsight
4. Oracle Stream Analytics, Autonomous DB (partly open core, based on Spark)
5. Quix Analytics Quix

6. SAP Leonardo Edge Services
7. SAS Event Stream Processing
8. Software AG Cumulocity IoT Analytics (Apama)
9. TIBCO Streaming, Cloud Integration (Business Events)