Now presents bi-directional integration with Iceberg, sooner vector search, enhanced full-text search, autoscaling and a “carry your personal cloud” deployment
SingleStore, the real-time information platform so that you can transact, analyze and contextualize, introduced a bi-directional integration with Apache Iceberg that opens up a world of alternatives for constructing clever purposes on information lakehouses. This integration addresses the important problem confronted by enterprises the place an estimated 90% of knowledge stays “frozen” in lakehouses and is unusable for powering interactive purposes, analytics or AI.
Apache Iceberg is the de facto customary for information lakes for storing huge datasets, providing value effectivity for querying large-scale datasets. Nevertheless, enterprises battle to leverage this information because of advanced, expensive processes required to ‘thaw’ it, together with intensive ETL workflows and compute-intensive Spark jobs.
SingleStore’s new integration is meant to resolve exactly that, offering low-latency ingestion, bi-directional information move and real-time software efficiency at decrease prices for contemporary clever purposes and analytics. This providing is out there in public preview as we speak and prospects will quickly be capable of create exterior tables in SingleStore based mostly on Iceberg information, construct projections on these tables and benefit from the velocity and efficiency of SingleStore on frozen information.
SingleStore’s prospects, lots of whom use Apache Iceberg for his or her information lakes and industrial lakehouses, have expressed a powerful curiosity in an answer that permits quick interactive purposes and low-latency analytics utilizing their huge, untapped Iceberg information.
“Our imaginative and prescient has at all times been to offer one single information retailer for all firms to have the ability to benefit from velocity, scale and ease,” stated Raj Verma, CEO, SingleStore. “Our information platform is designed to unlock all forms of enterprise information — together with information that’s frozen in information lakes — to allow our prospects to construct fashionable clever apps. With this launch, we consider we’re enabling a good portion of the market that as we speak can’t construct real-time fashionable purposes on information saved in information lakes.”
Other than the Iceberg integration, SingleStore additionally introduced a slew of different new options and product enhancements that allow constructing enterprise-grade clever purposes, together with:
● Sooner vector search. Vector search with HNSW is 40% sooner in comparison with the sooner launch. SingleStore’s IVF Flat index is demonstrated to be between 47 to 100x sooner than pgvector, and vector index construct instances are actually 2-3x sooner than Milvus and pgvector. Extra vector search options embrace vary searches and filters (in public preview) to assist enterprises simply construct and scale generative AI purposes.
● Enhanced full-text search. SingleStore has supported full-text seek for numerous years. With its June 2024 launch, the corporate is saying the final availability of sturdy new capabilities in full-text search together with improved relevance scoring, phonetic similarity, fuzzy matching and keyword-proximity-based rating. All this implies organizations can now simplify their information architectures by eliminating the necessity for added specialty databases to construct generative AI and real-time purposes.
● Autoscaling. With compute workspaces and a distributed structure, SingleStore is a extremely scalable information platform. With Autoscaling in its newest launch (in public preview) prospects guarantee software efficiency by scaling compute sources up or down robotically in seconds to regulate to unpredictable workloads — whereas avoiding billing surprises.
● Helios® — Convey Your Personal Cloud (BYOC) deployment. For a lot of prospects, their information has to stay in their very own digital non-public cloud (VPC), underneath their very own safety and governance insurance policies due to regulatory necessities or contractual obligations. In these instances prospects needed to deploy SingleStore in a self-managed mannequin, managing operations themselves. With this announcement, SingleStore is introducing a fully-managed cloud providing (Helios — BYOC), that lets prospects benefit from the ease of administration and elastic scalability of the platform, however inside their very own digital non-public cloud. This providing is now obtainable in non-public preview in AWS, and prospects can run SingleStore in their very own tenants whereas complying with information residency and governance insurance policies.
“SingleStore’s information platform is indispensable for analyzing our information and delivering real-time insights to our prospects,” stated Mauricio Aristizabal, Principal Information Architect, impression.com, and Founder, Giist Social. “This newest replace continues to push the boundaries of what we are able to accomplish by harnessing all of our enterprise information in actual time. We’re trying ahead to leveraging the newest cutting-edge options to proceed rising our and our purchasers’ enterprise.”
“Our new options and capabilities advance SingleStore’s mission of providing a real-time information platform for the following wave of generative AI and information purposes,” stated Nadeem Asghar, Head of Engineering at SingleStore. “The combination with Iceberg, plus enhancing our platform’s scaling and processing capabilities will permit customers to entry and harness their information in actual time, and construct clever apps.”
SingleStore stays on the forefront of generative AI innovation. The corporate’s product innovation has led to high-momentum progress in prospects, pushing it to surpass $100M in ARR on the finish of 2023. SingleStore was acknowledged with 5 2024 TrustRadius Prime Rated Awards, probably the most the corporate has ever gained in a single 12 months. 4 awards had been gained for the third consecutive 12 months, whereas the popularity within the Vector Database class was a primary.
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