Confluent vs. IBM in the Data Streaming Market: What Investors Need to Know

The data streaming market has become a battleground for enterprise software leaders, with Confluent and IBM positioning themselves at the forefront. With real-time data becoming increasingly crucial for businesses across industries, the question of who will dominate this space—and what it means for investors—is more relevant than ever. This year, Confluent has shown strong growth and innovation, while IBM continues to rely on its long-standing enterprise relationships and robust cloud infrastructure. Understanding their positions and strategies is key for any investor keeping an eye on the evolving data infrastructure sector.

Understanding the Landscape of Data Streaming and Market Players

At its core,

data streaming refers to the continuous flow of data from various sources to applications, allowing organizations to act on insights in real time. Apache Kafka, which Confluent was built on, is one of the foundational technologies in this space. Confluent has evolved it into a full-fledged platform, while IBM has leaned on its broader enterprise software ecosystem, including IBM Cloud and IBM Data and AI, to offer competitive solutions.

The market is also seeing rapid growth. For example, the data pipeline tools market was valued at USD 13.82 billion in 2025 and is projected to exceed USD 66.18 billion by 2033, growing at a 21.63% CAGR. Real-time data pipeline adoption is particularly surging, with a CAGR of 25.11%. These numbers highlight why companies like Confluent and IBM are investing heavily in this area.

Confluent's Recent Momentum and Strategic Moves

Confluent has been gaining traction with both its product development and strategic vision. In the most recent quarter, the company reported 19% year-over-year revenue growth, exceeding analyst expectations. This success is being driven by its expansion into AI-focused data streaming. For instance, Confluent recently introduced Intelligence features and a new private cloud solution tailored for regulated industries.

In addition, Confluent has drawn attention from investors and analysts. Jackson Peak Capital has named Confluent as its largest position and a high-conviction event-driven idea, suggesting the company is on its way to becoming a top-tier data infrastructure player. The firm has also highlighted the possibility of an acquisition, which could further accelerate Confluent's growth.

IBM's Position and Approach in Data Streaming

IBM, while not as agile or product-focused as some of its rivals, brings decades of enterprise experience and a broad ecosystem. The company's approach to data streaming is more integrated with its broader AI and cloud strategy. For example, IBM Cloud Pak for Data is a key offering that includes data streaming capabilities as part of a larger enterprise data platform. IBM also benefits from its long-standing relationships with large corporations and government agencies.

That said, IBM faces challenges in a market that’s shifting toward cloud-native and open-source solutions. The rise of DataOps, with its agile and collaborative approach to data pipeline development, is making it harder for traditional vendors to maintain their dominance. In the ISG Buyers Guide™ for DataOps, IBM was not among the top leaders in Data Pipeline tools, while Databricks and Informatica took the lead.

What This Means for Investors and the Broader Market

For investors, the key takeaway is that the data streaming market is still in its growth phase and is likely to be shaped by innovation and product differentiation. Confluent's recent performance and product roadmap suggest it could continue gaining market share, especially as more companies adopt real-time data for AI applications. IBM, on the other hand, may rely more on its ecosystem and enterprise partnerships to maintain its presence.

The broader market is also evolving. More than half of enterprises are expected to adopt DataOps practices by 2027, which will likely favor platforms that support automation, collaboration, and real-time analytics. In this context, companies like Confluent and IBM will need to adapt their strategies to stay competitive.

Looking Ahead: Trends and Opportunities in 2026

Looking ahead, the coming year is likely to bring more competition in the data streaming space. As AI adoption grows, the demand for real-time data pipelines will only increase. The market is also being shaped by new players and technologies, such as Databricks Asset Bundles and Lakeflow Connect, which are streamlining data engineering workflows.

Meanwhile, the rise of cloud-native solutions and the shift toward open-source frameworks like Apache Kafka suggest that companies with strong platform ecosystems—like Confluent—may gain a long-term edge. IBM will need to continue leveraging its enterprise expertise while also integrating more modern, cloud-native tools to remain relevant.

At the end of the day, investors should keep a close eye on both companies' ability to innovate and scale. The data streaming market is still in its early innings, and the players that can best meet the needs of AI-driven enterprises are likely to see the strongest returns.