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Kinetica Delivers Real-Time Vector Similarity SearchKinetica accelerates vector similarity search with NVIDIA RAPIDS RAFT SAN JOSE, Calif., March 20, 2024 (GLOBE NEWSWIRE) -- Kinetica, the real-time GPU-accelerated database for analytics and generative AI, today unveiled at NVIDIA GTC the industry’s only real-time vector similarity search engine that can ingest vector embeddings 5X faster than the previous market leader, based on the popular VectorDBBench benchmark. Under the hood Kinetica uses NVIDIA RAPIDS RAFT to harness the power of the GPU for vector similarity search. With Kinetica’s best-in-class combined data and query latency for vector embedding pipelines, large language models (LLM) can immediately augment their results with new information via embeddings as soon as they are generated, without delays at scale. Goldman Sachs Research estimates the total addressable market for generative AI software to be $150 billion. As more generative AI tools are developed and layered into existing software packages and technology platforms, businesses across the economy have the potential to realize tremendous benefits. Unlike existing vector databases that suffer from data latency issues, Kinetica’s innovative ability to leverage the GPU in real-time ensures access to the latest data, empowering applications with unparalleled speed, accuracy, and responsiveness. Its capacity to deliver instant insights amid data growth and change presents a groundbreaking solution for industries reliant on quick and up-to-date AI-driven analytics. “At Kinetica, our focus has always been on delivering real-time insights in a rapidly evolving data landscape through our natively vectorized GPU optimized architecture,” said Nima Negahban, Cofounder and CEO, Kinetica. “The introduction of real-time vector similarity search for pattern and anomaly detection perfectly aligns with our technology foundation and underscores our position at the forefront of data-driven innovation.” Real-time vector similarity search also opens up new applications in domains for retrieval augmented generation (RAG) that are beyond just language and rich media. Vector embeddings of time series and spatial data can capture features and patterns that convey meaning about time-variant phenomena like stock rices, weather, and objects in motion. A real-time similarity search engine can immediately identify temporal trends, spatial patterns and anomalies as they occur making it suitable for various use cases where real-time insights on numerical data are crucial for informed decision-making and predictive analytics. “While other vendors offer vector-only databases as a product, our approach integrates vector search as a powerful feature within our mature, distributed, secure, and ANSI SQL compliant database, providing enterprises with a comprehensive solution for data analytics.” said Amit Vij, Cofounder and President, Kinetica. Key Features of Kinetica Vectorization:
DJ Patil, General Partner, Great Point Ventures says that realizing generative AI’s potential will require developing capabilities around high-speed data. “Most of the stuff we see around LLMs today is low-speed data; it’s very static, and it hasn’t been updated,” he says. “We haven’t yet figured out the applications for AI that are going to show up with this higher speed of sensor data. That’s something I think we’re going to see develop over the next 24 months.” By leveraging NVIDIA RAPIDS RAFT vector search algorithms in conjunction with its own internal data management systems, Kinetica empowers businesses to achieve lightning-fast, real-time vector search, enabling them to glean actionable insights from their data with remarkable speed and efficiency. “In the era of accelerated computing, Kinetica is integrating NVIDIA RAPIDS into its GPU accelerated, real-time database,” said John Zedlewski, Senior Director of Accelerated Data Science, NVIDIA. “By taking advantage of NVIDIA RAPIDS vector search, Kinetica can offer higher throughput, lower latency and faster index builds for Gen AI applications.” Availability Kinetica’s vector similarity search is now available in Kinetica 7.2 for users of Kinetica Cloud Dedicated, Developer Edition, and Kinetica Enterprise. About Kinetica Media Contact: |