Confluent placed as a ‘Niche Player’ in the 2023 Gartner® Magic Quadrant™ for Data Integration Tools

Gartner has placed Confluent as a “Niche Player” in the 2023 Gartner Data Integration Tools Magic Quadrant*, noting this key strength: “Depth of data streaming/Apache Kafka understanding and support: Confluent has comprehensive stand-alone and fully managed service offerings for Apache Kafka, enabling highly performant data streaming pipelines.”

We are extremely proud of this recognition of our commitment to providing our customers with the best-in-class real-time data streaming platform. Real-time data streaming enables companies to make informed decisions based on the latest data, leading to better business outcomes. Customers across industries depend on data streaming in today’s fast-paced world, from a traditional retail giant such as Walmart, monitoring inventory levels to ensure stores never run out of items, or a cloud-native financial services firm like 10x Banking, building cutting-edge out-of-the-box banking solutions for traditional retail banks  Real-time data streaming and processing are at the center of powering all these workflows. 

Reinventing Apache Kafka® for the data streaming era, Confluent connects and processes all our customer data in real-time with a cloud-native and complete data streaming platform available everywhere and for every use case. 

Gartner says, “Kafka is difficult to manage at scale, requiring steep learning curves for operational teams and developers. Confluent offers a fully managed Kafka service, allowing clients to focus on data integration pipelines. Tools like Schema Registry, ksqlDB, and Stream Designer enable developers and architects to build complex streaming pipelines.”

The Emergence of Real-Time Data 

This moment in time is also a reflection of the maturity of data streaming vs. legacy batch processing. Apache Kafka, the de facto standard for real-time streaming, takes batch and streaming data sets as streaming tables. These tables can be referenced and consumed either in real time or in batch as request-response based on the needs of the use case and downstream consumers or systems. 

But a batch system cannot support any real-time use case, and it’s why we say batch is a subset of streaming. Batch processing is limited to non-real-time data processing while streaming is a more generalized and flexible approach. 

As businesses become more reliant on real-time data processing, building an architecture based on batch processing may not be sufficient for future requirements. Batch processing can lead to consistency issues due to delays in system updates, which can result in departments working with inconsistent data. The overall latency of the system is the sum of the latency of all systems involved in the processing and distribution of data. Therefore, considering consistency and real-time requirements is imperative when choosing an appropriate data processing architecture. At Confluent, we recognize the importance of real-time data processing and have transformed Apache Kafka into the world’s leading data streaming platform.

A New Paradigm: Data Streaming Platform

Today, companies are under more pressure than ever to deliver the real-time experiences that today’s customers demand. The information required to power these experiences is stuck in a data mess—an increasingly complex web of batch-oriented, custom code integrations across many systems, apps, and databases. 

Data streaming platforms are the key to turning this data mess into data value. This isn’t just bolting on more tech or moving into a central data store. It’s a software platform that transforms your existing network of silos and batch systems into a system of data in motion so that you can create real-time experiences faster and more cost-effectively than ever. A data streaming platform enables real-time streaming across the organization in a fast, safe, and cost-effective manner. It connects and unlocks all your enterprise data from source systems and serves it as continuously streamed, processed, and governed data products. These real-time data products are instantly valuable, trustworthy, and reusable and ensure your data is used in a consistent manner everywhere it’s needed. 

This approach unleashes a virtuous cycle of innovation, with each new data product increasing the value of the others and enabling more reuse across the organization. It changes your focus from “where is my data, and is it accurate” to “what is my data, and how do I get value from it immediately.” Data streaming platforms connect all your applications, systems, and teams with a shared view of the most up-to-date, real-time data.

Confluent is the only data streaming platform that delivers on all four fundamental principles to a successful streaming service—to stream, connect, process, and govern data. It’s why we say Confluent is the world’s leading data streaming platform.

Stream:  Streaming is at the heart of our platform. We transformed Kafka with Kora engine, our Apache Kafka engine built for the cloud. Kora abstracts all the operational challenges of self-managing Kafka and delivers a fully managed, cost-effective Kafka service. Kora powers Confluent Cloud to support streaming across 30,000+ clusters around the globe. Kora is elastic, resilient, cost-efficient, and runs at low latencies.

Connect: Our connector ecosystem enables customers to connect to any data source and sink—wherever they reside—including databases, message queues, cloud services, and more! We support over 120+ pre-built connectors and 70+ fully managed connectors. We’ll also manage your custom connectors to homegrown systems and apps. 

Process: Stream processing combines multiple data streams and shapes them on the fly to drive greater data reuse. Confluent supports SQL-based stream processing and recently announced the public preview of Apache Flink® on Confluent Cloud. Flink has emerged as the de facto stream processing standard, and Confluent has gone beyond cloud-hosted Flink to build a truly cloud-native, serverless stream processing service. 

Govern: We offer the only fully managed governance suite for data in motion. Stream Governance allows you to catalog streams as data products—so you can apply data quality controls, compliance standards, and maintain usage visibility while making streams available for anyone in your organization to discover and consume. Furthermore, Confluent offers built-in security tools, including granular RBAC, cloud audit logs, private networking capabilities, data encryption at rest and in transit, and much more. 

With these four principles, we take data from your data mess and turn it into reusable, high-quality data products. These data products can then be shared and used to build custom applications that deliver real-time experiences for customers and other data systems.

At Confluent, we are committed to our customers' success. Our real-time data streaming capabilities enable our customers to build innovative applications and make informed decisions based on the latest data. We are proud of Gartner’s recognition of our streaming capabilities, and our placement as a Niche Player in the 2023 Gartner Data Integration Tools Magic Quadrant.

A thank you to our customers, partners, and community

We’re excited to share this recognition with our customers, our broad partner ecosystem, and the open-source community of developers. Without their feedback, input, and contributions, we couldn’t deliver the value we do today. Thank you!

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache® and Apache Kafka® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by using these marks. All other trademarks are the property of their respective owners.

* 2023 Gartner Magic Quadrant for Data Integration Tools, 4 December 2023 

Authors: Ehtisham Zaidi, Robert Thanaraj, et al.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.