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Top 5 Event Stream Processing Software SaaS Companies in May 2026

As of May 2026, there are 5 SaaS companies in Event Stream Processing Software. They have combined revenues of $119.1M and employ 711 people. They have raised $7M and serve 1K customers combined.

Event Stream Processing Software is designed to manage and analyze continuous streams of data in real time. This category of software enables organizations to capture, process, and react to events as they occur, allowing for immediate decision-making and action. Primary use cases include monitoring system performance, real-time analytics, and automating responses to operational changes in various industries such as finance, e-commerce, and telecommunications. Typical features of event stream processing software include event ingestion from multiple sources, data enrichment, real-time analytics, and data visualization capabilities. Users often include IT operations teams, data engineers, and business analysts, all needing to handle and derive insights from streaming data effectively. By optimizing data processing workflows, these tools support organizations in becoming more responsive and data-driven in their decision-making processes.

Companies
5
Revenue
$119.1M
Funding
$7M
Employees
711

Filters

Sorting: Highest -> Lowest

Filters

Top Event Stream Processing Software Companies

Showing 10 of 2 companies ranked by annual revenue.

1
3cket

Lisbon, Portugal

3cket is reshaping events with cutting-edge technology. Our technology empowers event organizers, agencies and brands to create unforgettable experiences, delivering innovative ticketing and payment solutions, management tools and analytics for any event.

Revenue
$5M
Customers
1K
Year founded
2019
Funding
-
Team size
19
Growth
-
2
Arroyo

Berkeley, California, United States

Cloud-native stream processing

Revenue
$5M
Customers
-
Year founded
2022
Funding
-
Team size
2
Growth
-

Inclusion Criteria

- The software must enable real-time processing of continuous data streams. - It should support multiple data sources including applications, IoT devices, and databases. - Must provide analytics capabilities to derive actionable insights from streaming data. - Should include features for event transformation and enrichment during processing. - Not just a data storage solution; must actively process and act on the incoming data streams.