DataStax, the well-funded Apache Cassandra-centric database company, is making significant investments in AI technology. The company believes that AI has the potential to provide highly scalable vector search capabilities, which can offer real-time context to generative AI models. Today, after a brief public preview, DataStax is launching the vector search capabilities of its Astra DB service into general availability.
Vector databases have emerged as a foundational technology for generative AI. According to DataStax CPO Ed Anuff, this is the most exciting development for databases in a long time. Databases now have the opportunity to provide memory for artificial intelligence, a significant shift in their purpose and importance.
DataStax customers can now utilize Astra DB’s vector search capabilities on major cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform. The service was originally launched on these platforms. DataStax Enterprises users who run the service in their own data centers will have access to vector search within the next month.
During the preview period, DataStax observed substantial adoption and active usage of the product. Customers who use vector search tend to be highly engaged users. Within a few days after the public preview launch, DataStax received over 1,000 signups. In the same week, the company began 50 new major enterprise proof-of-concept projects.
DataStax believes it has a competitive advantage due to its core technology based on Apache Cassandra. This technology enables its database index to achieve massive scalability, meeting the demands of various use cases. Additionally, DataStax holds a wide range of certifications, further solidifying its position in the market. Furthermore, Astra DB now supports the LangChain framework for building LLM-based applications.
Generative AI has gained significant attention, and vector search plays a crucial role in enhancing these AI models with recent or personalized data. Consequently, other database services are also capitalizing on this momentum. However, DataStax claims that its technology and certifications provide an edge in the market.
Matt Aslett, VP and Research Director at Ventana Research, explains that the ability to trust the output of generative AI models is essential for enterprise adoption. By incorporating vector embeddings and search capabilities into existing data platforms, organizations can augment generic models with enterprise information and data, alleviating concerns about accuracy and trust.
DataStax’s launch of vector search capabilities for Astra DB demonstrates the company’s commitment to leveraging AI technology for scalable and real-time database solutions. With its robust technology and growing customer base, DataStax is positioned to play a major role in the evolving landscape of generative AI and vector databases.
