IBM announced the acquisition of DataStax, a provider of AI and data technologies. DataStax’s technology strengthens IBM’s watsonx portfolio and accelerates the use of generative AI.
The acquisition fits into IBM’s open-source portfolio. DataStax is the developer of AstraDB and DataStax Enterprise, NoSQL and vector database solutions based on Apache Cassandra, and Langflow. That is an open-source tool and community for low-code AI application development.
IBM continues to support and engage the open-source communities around Apache Cassandra, Langflow, Apache Pulsar and OpenSearch for innovations. IBM’s commitment to open-source AI also includes the IBM Granite foundation models and Instruct Lab, an innovative approach to open-source innovation on Large Language Models (LLMs).
Leveraging untapped unstructured data
Companies struggle with effectively leveraging unstructured data, essential for generative AI. Without the right tools to process and manage this data properly, costly AI projects do not reach their full potential. According to McKinsey, even 70% of companies with successful generative AI initiatives experience data-related challenges. Moreover, researchers estimate companies only leverage 1% of their data in AI models.
IBM helps organizations adopt generative AI at scale and transform their business operations with enterprise data. The acquisition of DataStax strengthens these efforts. For example, DataStax’s vector database makes it easier to leverage unstructured data and accelerates value creation. Langflow provides a visual, low-code design tool and component orchestration for generative AI apps, facilitating collaboration among diverse teams.
Product-ready GenAI applications.
AstraDB and DataStax Enterprise provide NoSQL and vector database capabilities based on Apache Cassandra. This enables production-ready generative AI applications. AstraDB extends the existing vector functionality of IBM watsonx.data – IBM’s hybrid, open data lakehouse for AI and analytics. Many organisations already use Apache Cassandra, including big names in the software, retail, financial and e-commerce sectors. Apache Cassandra is increasingly used for AI workloads thanks to its scalability, availability, fault tolerance and support for hybrid cloud environments.
In this context, DataStax combines a database solution with vector and graphRAG functionalities to maximize the use of unstructured data for generative AI.
Langflow, a low-code open-source app builder for RAG and multi-agent AI applications, is Python-based and compatible with various models, APIs and databases. Langflow will add additional middleware functionality to IBM watsonx.ai, IBM’s integrated AI development studio for generative AI applications.
Tip: IBM marries AI platform with as much data as possible: what’s Watsonx?