Best Event Stream Processing Software for Confluent

Compare the Top Event Stream Processing Software that integrates with Confluent as of March 2026

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This a list of Event Stream Processing software that integrates with Confluent. Use the filters on the left to add additional filters for products that have integrations with Confluent. View the products that work with Confluent in the table below.

What is Event Stream Processing Software for Confluent?

Event stream processing software enables organizations to analyze and process data in real-time as it is generated, providing immediate insights and enabling quick decision-making. This software is designed to handle large volumes of streaming data, such as sensor data, transaction logs, social media feeds, or financial market data. Event stream processing software often includes features like real-time analytics, pattern detection, event filtering, and aggregation to identify trends or anomalies. It is widely used in applications such as fraud detection, predictive maintenance, supply chain management, and real-time analytics. Compare and read user reviews of the best Event Stream Processing software for Confluent currently available using the table below. This list is updated regularly.

1

Ably

Ably

Ably is the definitive realtime experience platform. We power more WebSocket connections than any other pub/sub platform, serving over a billion devices monthly. Businesses like HubSpot, NASCAR and Webflow trust us to power their critical applications - reliably, securely and at serious scale. Ably’s products place composable realtime in the hands of developers. Simple APIs and SDKs for every tech stack, enable the creation of a host of live experiences - including chat, collaboration, notifications, broadcast and fan engagement. All powered by our scalable infrastructure.

Starting Price: $49.99/month

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2

kPow

Factor House

We know how easy Apache Kafka® can be with the right tools. We built kPow to make the developer experience with Kafka simple and enjoyable, and to save businesses time and money while growing their Kafka expertise. kPow allows you to get to the heart of production issues in clicks, not hours. Search tens of thousands of messages a second with kPow’s powerful Data Inspect and kREPL functions. New to Kafka? kPow’s unique Kafka UI allows developers to quickly and easily understand core Kafka concepts and gotchas. Upskill new team members, and grow your internal Kafka expertise. kPow provides a suite of Kafka management and monitoring features in a single Docker Container or JAR file. Manage multiple clusters, schema registries, and connect installs with one instance.

Starting Price: $2,650 per cluster per year

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3

Lenses

Lenses.io

Enable everyone to discover and observe streaming data. Sharing, documenting and cataloging your data can increase productivity by up to 95%. Then from data, build apps for production use cases. Apply a data-centric security model to cover all the gaps of open source technology, and address data privacy. Provide secure and low-code data pipeline capabilities. Eliminate all darkness and offer unparalleled observability in data and apps. Unify your data mesh and data technologies and be confident with open source in production. Lenses is the highest rated product for real-time stream analytics according to independent third party reviews. With feedback from our community and thousands of engineering hours invested, we've built features that ensure you can focus on what drives value from your real time data. Deploy and run SQL-based real time applications over any Kafka Connect or Kubernetes infrastructure including AWS EKS.

Starting Price: $49 per month

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4

Arroyo

Arroyo

Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.

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