Planned acquisition furthers IBM’s commitment to open-source innovation; helps clients access untapped, unstructured enterprise data to maximize the impact of generative AI
IBM announced its intent to acquire DataStax, a leading provider of AI and data solutions. This strategic move aims to enhance IBM’s watsonx portfolio, accelerating the adoption of generative AI and enabling businesses to unlock insights from vast amounts of unstructured data.
Expanding IBM’s Open-Source AI Commitment
The acquisition reinforces IBM’s dedication to open-source AI. DataStax is known for developing AstraDB and DataStax Enterprise, which offer NoSQL and vector database capabilities powered by Apache Cassandra®, along with Langflow, an open-source tool and community designed for low-code AI application development.
IBM will continue its active participation and innovation within the open-source communities of Apache Cassandra®, Langflow, Apache Pulsar™, and OpenSearch, where DataStax has played a key role. This aligns with IBM’s broader commitment to open-source AI, which includes its IBM Granite foundation models and Instruct Lab, a pioneering initiative aimed at driving true open-source innovation for large language models (LLMs).
Unlocking the Power of Unstructured Data for Enterprises
Organizations face significant challenges in harnessing unstructured data across their operations—data that is crucial for driving generative AI. Without efficient tools for data ingestion and management, generative AI projects risk underperforming. According to McKinsey, even 70% of companies with high-performing generative AI initiatives struggle with data-related challenges, and only a fraction—around one percent—of enterprise data is currently represented in AI models.
IBM has a strong track record in helping businesses scale generative AI solutions by leveraging enterprise data. The acquisition of DataStax enhances these capabilities, as its vector database technology enables the efficient processing of unstructured enterprise data, accelerating its time to value. Meanwhile, Langflow offers a graphical, low-code design environment that streamlines component orchestration for generative AI applications, fostering collaboration among teams with varying technical expertise.
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Advanced AI-Ready Databases for the Enterprise
AstraDB and DataStax Enterprise deliver NoSQL and vector database capabilities powered by Apache Cassandra®, making them essential for building production-ready generative AI applications. By integrating AstraDB’s capabilities into IBM watsonx.data—IBM’s hybrid, open data lakehouse for AI and analytics—IBM strengthens its data infrastructure for AI-driven solutions.
Apache Cassandra® is widely used across industries, supporting some of the largest names in software, retail, finance, and e-commerce. Known for its scalability, fault tolerance, high performance, and hybrid cloud support, Apache Cassandra® is increasingly being utilized for AI workloads. In this landscape, DataStax offers a mature datastore with advanced vector and graphRAG capabilities—an essential combination for leveraging unstructured data in generative AI.
Langflow, a low-code, open-source app builder, enables the development of retrieval-augmented generation (RAG) and multi-agent AI applications. Built on Python, Langflow is designed to be model-, API-, and database-agnostic. This flexibility enhances IBM watsonx.ai, IBM’s end-to-end AI development studio, by providing additional middleware capabilities essential for generative AI development.
“Businesses cannot realize the full potential of generative AI without the right infrastructure – open-source tools and technologies that empower developers, harness unstructured data, and provide a strong foundation for AI applications,” says Dinesh Nirmal, Senior Vice President, IBM Software. “DataStax possesses deep competency in this area and shares IBM’s relentless commitment to simplifying and scaling generative AI for the enterprise.”
“Enterprises want to deliver production AI fast, but are still struggling to unlock the value in their data to power AI applications and agents,” says Chet Kapoor, Chairman and CEO of DataStax. “DataStax’s products solve this problem, accelerating AI’s promise with the scalability, security, and accuracy developers and enterprises need. We’ve long said that there is no AI without data, and are excited to execute this vision with IBM.”
