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IBM to Acquire DataStax, Boosting Generative AI and Unstructured Data Solutions

Big Data

Business Honor
26 Febuary, 2025

Acquisition strengthens IBM’s AI capabilities, enabling businesses to unlock unstructured data potential.

IBM (NYSE: IBM) has announced its intention to acquire DataStax, a leader in AI and data solutions, in a move that will further bolster the capabilities of IBM’s watsonx portfolio. This acquisition is set to accelerate the use of generative AI, enabling enterprises to unlock value from vast, unstructured data that currently poses a significant challenge.

DataStax’s technologies, including AstraDB and DataStax Enterprise, offer NoSQL and vector database solutions powered by Apache Cassandra^®, a crucial database for enterprises requiring scalability, high performance, and robust AI integration. These tools are integral for businesses struggling to harness unstructured data to power generative AI applications. IBM’s acquisition will enhance its ability to provide enterprises with the infrastructure needed to scale AI and analytics efficiently.

Additionally, DataStax’s Langflow, an open-source, low-code tool, allows businesses to develop generative AI applications with ease. Its flexible, Python-based environment helps developers rapidly build and deploy AI applications, promoting collaboration across diverse teams. Langflow will complement IBM’s existing watsonx.ai, enhancing the development of production-ready AI solutions.

The acquisition of DataStax reflects IBM’s ongoing commitment to open-source AI and its focus on simplifying generative AI for the enterprise. As businesses face difficulties unlocking the value of their data—especially in the context of generative AI—DataStax’s solutions will address these challenges by ensuring organizations can leverage vast, unstructured datasets.

The move aligns with IBM’s strategy to support open-source technologies, particularly its efforts with Apache Cassandra^® and Langflow. According to McKinsey, 70% of companies with high-performing generative AI initiatives face data-related challenges, making IBM’s acquisition timely and strategic.

The deal, expected to close in Q2 2025, is subject to regulatory approvals and customary closing conditions.