Confluent Recognized in 2025 Gartner® Magic Quadrant™ for Data Integration Tools

We are pleased to announce that Confluent has been recognized again as a Challenger in the 2025 Gartner® Magic Quadrant™ for Data Integration Tools. We believe this recognition validates the scale and reliability of our platform, acknowledging our "Ability to Execute" in powering the mission-critical data flows of the world's largest organizations.

As we reflect on this year’s report, it has become increasingly clear that the market for data integration is bifurcating. On one side, there are traditional tools designed to connect static silos for historical analysis. On the other, there is the category of data streaming platforms (DSP); technologies engineered to set data in motion, enabling real-time responsiveness and operational intelligence.

While we are honored to be evaluated alongside traditional integration vendors, the reality is that we are running a different race.

Our DSP is delivering results. The question enterprises face today is not "How do we move data from A to B?" but rather "How do we make all parts of the business react together, in real time?" Traditional batch pipelines reconcile at the end of the day; a streaming platform lets you operate continuously.

• Customers are replacing fragmented batch ETL with unified streaming. 

  • Livestock Improvement Corporation (LIC), a New Zealand agricultural cooperative, replaced legacy batch pipelines with Confluent's streaming platform. 

  • The organization now delivers real-time herd health insights to 10,500 dairy farmers. Data that used to arrive in delayed batches now flows continuously, enabling faster decisions on breeding, health, and operations.

• We're making every engineer an AI engineer. 

  • With Streaming Agents and Real-Time Context Engine (part of Confluent Intelligence), developers build event-driven AI agents directly on Confluent Cloud for Apache Flink® using familiar APIs. 

  • These agents access fresh, enriched context at the moment decisions need to be made. An AI agent making decisions on stale data is an AI agent making wrong decisions. Our platform ensures the context feeding your agents is continuously updated, not hours old.

• We provide governance native to streaming. 

  • Stream lineage, schema management, and access controls are built for data in motion. This is not batch governance retrofitted to streams.

Intentional Design Choices: Streaming vs. Integration

The goalposts for the Data Integration Tools market are moving toward what Gartner calls "augmented" capabilities: generative AI interfaces designed to help users federate queries across static sources. But how you apply AI matters. Traditional tools use AI to patch together static silos and generate SQL for federated queries. The data remains stale. The silos remain silos. AI becomes a band-aid over architectural limitations. 

We believe AI should be a first-class citizen in the data itself. With Confluent Intelligence, AI operates directly on data in motion. Streaming Agents reason and act on events as they happen. Real-Time Context Engine serves fresh, enriched context to AI systems at the moment decisions need to be made. 

At Confluent, we have made deliberate design choices to prioritize developer experience, programmatic control, and low-latency processing over the drag-and-drop interfaces typical of legacy ETL tools.  This approach has been further validated by the ability to easily apply the natural language interface of generative AI (GenAI) for ease of use.

• We focus on universal access, not just virtualization. Gartner evaluates data virtualization, a method often used to patch together static silos for federated querying. While useful for ad-hoc analysis, this approach often struggles with performance at scale. We believe the better answer is open standards. With Tableflow, we allow Apache Kafka® topics to be accessed instantly as Apache IcebergTM or Delta Lake tables. This delivers the primary benefit of virtualization (i.e., making data easily queryable by engines against fresh data) but ensures that the underlying foundation can support modern analytical and AI work loads at any scale with any tool in the modern stack, not just a proprietary virtualization layer.

• We aren't just doing batch; we are unifying it. Historically, "batch" and "streaming" required different tools, different skills, and different pipelines. With Confluent Cloud for Apache Flink®, we are blurring these lines. We treat batch as bounded data processing, a subset of streaming, allowing developers to write code once and run it anywhere. 

• We treat data as something to be reasoned about continuously. Legacy integration tools treat data as something to be moved in steps: extract it, transform it, load it somewhere else. With Confluent’s stream processing capabilities, your logic lives with the data, operating on it as it flows. Write once, run on any data, at any speed.

Bridging the Gap: Tableflow and the Modern Data Stack

We recognize that data streaming does not exist in a vacuum. It must connect seamlessly with the data lakes and data warehouses that power your analytics. This is why we built Tableflow, a feature that allows Kafka topics to be materialized instantly as open table formats. 

With Tableflow, streaming data is simply there: fresh, high-quality, and instantly accessible to any platform that supports Iceberg or Delta Lake. Topics are automatically discoverable in leading analytical catalogs like Apache Polaris, Databricks Unity, and AWS Glue. There is no pipeline to build. There is no ETL to maintain. The data arrives in the format your analytical tools expect, at the moment they need it.

Tableflow represents our vision of modern integration: something considerably greater than building brittle point-to-point pipelines to move data from A to B. Our data streaming platform makes streaming data instantly available for analytics in tools like Snowflake and Databricks, without the "heavy lifting" of traditional ETL.

Confluent continues to invest across deployment options so teams can run data streaming wherever their applications live with the security, networking, and reliability profile each use case demands. Our DSP brings elastic capacity and operational simplicity in Confluent Cloud together with enterprise-grade capabilities in Confluent Platform and private environments, making every workload easier to build, operate, and scale without locking you into a single architecture.

We meet teams where they are. Whether you need fully managed cloud, bring-your-own-cloud or private cloud for data sovereignty, or self-managed for maximum control, our platform delivers consistent capabilities across every deployment model with pricing that scales with your adoption.

Looking Ahead

We appreciate Gartner’s work in analyzing the diverse and complex Data Integration market. Our placement in this year’s Magic Quadrant underscores our commitment to execution and reliability. But make no mistake: our eyes are fixed on the future of data streaming platforms.

We will continue to build for the data streaming engineers, architects, and builders who are constructing the real-time applications of tomorrow. We aren't just integrating your data; we are setting it in motion.

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

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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

Apache®, Apache Kafka®, Kafka®, Apache Flink®, Flink®, Apache IcebergTM, IcebergTM, and the Iceberg, Kafka, and Flink logos  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.