While innovations in the business world have always resulted in a scramble to adopt the technologies that enable them, the generative AI boom has seen a rush like no other in recent history. Generative AI promises to allow organizations to make transformations quickly, across the entirety of their internal and customer ecosystem.
However, real-time insights require technologies that operate in real time. To that end, SingleStore has just released a series of product innovations that aim to put real-time AI capabilities in the hands of its customers.
SingleStore is on the Acceleration Economy Top 10 Shortlist of Data Modernization Enablers.
What’s New at SingleStore?
At SingleStore Now: The Real-time AI Conference in San Francisco, the company made a series of announcements that collectively demonstrated how it will enable real-time AI capabilities at enterprise scale. While SingleStore has long provided its customers with real-time app and analytics delivery, this tried-and-tested functionality is now expanding to AI use cases.
“These products were innovated with one thing in mind: making the vision of real-time AI a reality for customers with huge amounts of data,” said Raj Verma, SingleStore CEO, in detaling the announcements. “We’re incredibly excited that these products are taking giant strides in the right direction and that SingleStore remains the sole contextual database in the market to elevate data to information through context – a key to unlocking the power of real-time AI.”
So what are the new product innovations, and how will they benefit SingleStore customers?
SingleStore Scope: Addressing the need for efficient indexing to manage the vast scale of unstructured data used in AI development, particularly generative AI, Scope enables hybrid search. The tool combines fast vector search, full-text search, and a range of indexing techniques to support Approximate Nearest Neighbor (ANN) search, a powerful method for speeding up search results developed in the Big Data era.
SingleStore Aura compute service: Using this function, developers can deploy specific compute resources, such as CPUs and GPUs, optimized for AI/ML workloads alongside the data in their database. Described as part of an intelligence layer that sits between raw data and LLMs and also includes SingleStore Aura job service for job scheduling and SingleStore Radian data integration service, this functionality enables developers to feed data directly to LLMs and ML models without the risks associated with moving it.
SingleStore Notebooks: Another part of this intelligence layer is SingleStore Notebooks, which is now generally available. These web-based Jupyter notebooks enable developers to experiment with and collaborate on data analysis and workflows in SQL or Python. Notebooks have SingleStore’s AI chat bot SQL built-in, so code can be generated automatically, and developers can publish data products and APIs directly from the tool.
Alongside SingleStore Spaces, a series of prebuilt notebooks for specific use cases like generative AI development, Notebooks provides developers with the flexibility, efficiency, and collaborative structures needed to expedite AI workflows.
SingleStore Elegance: This new software development kit (SDK) enables developers to build full-stack, real-time AI apps, pre-configured to be compatible with SingleStoreDB. The technology is available via the React framework, and users can utilize prebuilt React components connected to their SingleStoreDB.
Power of Partners
SingleStore also announced expanded partnerships with a number of hyperscalers and new additions to its partners ecosystem to help its customers create applications more quickly and efficiently.
Major partnership expansions include developments with Google, with a new extension for Google Vertex AI. Regarding AWS, SingleStore announced a one-click deployment feature for LLM deployment on AWS via Amazon SageMaker. And, expanding their partnership with IBM, the company announced two new integrations for watsonx.
Ultimately, SingleStore has already proven its power in delivering real-time results. With this comprehensive series of announcements, the company is pursuing multiple avenues to bring real-time functionality to AI.
