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SingleStore Unveils New Offerings to Unfreeze Data Lakehouses, Powering Intelligent Applications

SingleStore Unveils New Offerings to Unfreeze Data Lakehouses, Powering Intelligent Applications

Now offers bi-directional integration with Iceberg, faster vector search, enhanced full-text search, autoscaling and a ‘bring your own cloud’ deployment

SingleStore, the real-time data platform for you to transact, analyze and contextualize, announced a bi-directional integration with Apache Iceberg that opens up a world of opportunities for building intelligent applications on data lakehouses. This integration addresses the critical challenge faced by enterprises where an estimated 90% of data remains “frozen” in lakehouses and is unusable for powering interactive applications, analytics or AI.

“Our vision has always been to provide one single data store for all companies to be able to take advantage of speed, scale and simplicity”

Apache Iceberg is the de facto standard for data lakes for storing massive datasets, offering cost efficiency for querying large-scale datasets. However, enterprises struggle to leverage this data due to complex, costly processes required to ‘thaw’ it, including extensive ETL workflows and compute-intensive Spark jobs.

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SingleStore’s new integration is intended to solve precisely that, providing low-latency ingestion, bi-directional data flow and real-time application performance at lower costs for modern intelligent applications and analytics. This offering is available in public preview today and customers will soon be able to create external tables in SingleStore based on Iceberg data, build projections on these tables and take advantage of the speed and performance of SingleStore on frozen data.

SingleStore’s customers, many of whom use Apache Iceberg for their data lakes and commercial lakehouses, have expressed a strong interest in a solution that enables fast interactive applications and low-latency analytics using their vast, untapped Iceberg data.

“Our vision has always been to provide one single data store for all companies to be able to take advantage of speed, scale and simplicity,” said Raj Verma, CEO, SingleStore. “Our data platform is designed to unlock all types of enterprise data — including data that is frozen in data lakes — to enable our customers to build modern intelligent apps. With this release, we believe we are enabling a significant portion of the market that today cannot build real-time modern applications on data stored in data lakes.”

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Apart from the Iceberg integration, SingleStore also announced a slew of other new features and product enhancements that enable building enterprise-grade intelligent applications, including:

  • Faster vector search. Vector search with HNSW is 40% faster compared to the earlier release. SingleStore’s IVF Flat index is demonstrated to be between 47 to 100x faster than pgvector, and vector index build times are now 2-3x faster than Milvus and pgvector. Additional vector search features include range searches and filters (in public preview) to help enterprises easily build and scale generative AI applications.
  • Enhanced full-text search. SingleStore has supported full-text search for a number of years. With its June 2024 release, the company is announcing the general availability of robust new capabilities in full-text search including improved relevance scoring, phonetic similarity, fuzzy matching and keyword-proximity-based ranking. All this means organizations can now simplify their data architectures by eliminating the need for additional specialty databases to build generative AI and real-time applications.
  • Autoscaling. With compute workspaces and a distributed architecture, SingleStore is a highly scalable data platform. With Autoscaling in its latest release (in public preview) customers ensure application performance by scaling compute resources up or down automatically in seconds to adjust to unpredictable workloads — while avoiding billing surprises.
  • Helios® — Bring Your Own Cloud (BYOC) deployment. For many customers, their data has to remain in their own virtual private cloud (VPC), under their own security and governance policies because of regulatory requirements or contractual obligations. In these cases customers had to deploy SingleStore in a self-managed model, managing operations themselves. With this announcement, SingleStore is introducing a fully-managed cloud offering (Helios — BYOC), that lets customers enjoy the ease of management and elastic scalability of the platform, but within their own virtual private cloud. This offering is now available in private preview in AWS, and customers can run SingleStore in their own tenants while complying with data residency and governance policies.

“SingleStore’s data platform is indispensable for analyzing our data and delivering real-time insights to our customers,” said Mauricio Aristizabal, Principal Data Architect, impact.com, and Founder, Giist Social. “This latest update continues to push the boundaries of what we can accomplish by harnessing all of our enterprise data in real time. We’re looking forward to leveraging the latest cutting-edge features to continue growing our and our clients’ business.”

“Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of generative AI and data applications,” said Nadeem Asghar, Head of Engineering at SingleStore. “The integration with Iceberg, plus enhancing our platform’s scaling and processing capabilities will allow users to access and harness their data in real time, and build intelligent apps.”

SingleStore remains at the forefront of generative AI innovation. The company’s product innovation has led to high-momentum growth in customers, pushing it to surpass $100M in ARR at the end of 2023. SingleStore was recognized with five 2024 TrustRadius Top Rated Awards, the most the company has ever won in a single year. Four awards were won for the third consecutive year, while the recognition in the Vector Database category was a first.

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[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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