Company ushers in a new era of real-time analytics and AI-powered search applications by significantly cutting compute costs; gets new investment from Hewlett Packard Enterprise
Rockset, the leading search and analytics database built for the cloud, announced a new instance class, resulting in 30% reduction in compute costs. This marks a bold stride towards the forefront of the real-time AI era that solidifies Rockset’s position as a global leader in cost-effective search and analytics databases.
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This new release makes Rockset the most affordable search and analytics database, offering a number of enhancements which include:
- General purpose instance class with different memory to CPU ratios optimized for low-cost search and AI applications.
- A lower entry price point to enable developers to start building real-time analytics and AI-powered search applications, as low as $232 per month.
- Autoscaling compute capabilities to scale compute based on the workload.
The momentum is further fueled by a strategic investment from Hewlett Packard Pathfinder, the venture capital program of Hewlett Packard Enterprise.
“We believe that the importance of real-time data analytics is intensifying, driven by the increasing demand we see from our customers for the most accurate and timely insights,” said Paul Glaser, vice president of Hewlett Packard Enterprise and head of Hewlett Packard Pathfinder. “Rockset is addressing the evolving demands with their advanced capabilities, extending search and analytics into vector search to provide AI and ML developers with rapid access to real-time data. We are excited to invest in Rockset and look forward to exploring joint customer opportunities.”
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As organizations break free from the constraints of legacy search engines like Elasticsearch, Rockset has emerged as a leading alternative for the cloud-native, AI-first era. Rockset’s search and analytics database is built for the cloud, with real-time indexing and full-featured SQL on vector embeddings, JSON, text, time series, and geospatial data.
“Indexing and searching across high dimensional vector embeddings can get very expensive very quickly. Rockset’s autoscaling capabilities allow users to scale their compute dynamically based on their workload. In addition, Rockset’s compute-compute separation allows users to decouple indexing compute from search query compute, unlocking massive efficiency and reliability wins,” said Rockset CEO and co-founder Venkat Venkataramani. “With the launch of our new general purpose instance class, Rockset is the most affordable and accessible search and analytics database in the world.”
Product Innovation Enables Real-Time Analytics and AI-Powered Search at Scale
This fiscal year, Rockset extended its search and analytics capabilities into vector search, offering AI and ML developers a game changing alternative that provides access to real-time data and fast queries with a fully managed cloud service. With approximate nearest neighbor (ANN) search, Rockset’s vector search capabilities enable billion-scale similarity search in the cloud, in a cost-effective way.
Additionally, Rockset introduced compute-compute separation, an industry-first for real-time analytics that eliminates compute overprovisioning by allowing streaming ingest or query serving to be independently scaled up and down, enabling multiple applications on shared real-time data without any operational burden.
Leading Enterprises Tap the Power of Real-Time Search, Analytics and AI Applications
Rockset’s customer base continues to expand as modern enterprises across the globe recognize the power of its search and analytics database to deploy AI applications at scale. The company now has over 300 customers including market leaders such as JetBlue, Meta, Whatnot, and Windward.
Rocket announced its partnership with Confluent as part of the Connect with Confluent partner program to help more organizations accelerate the development of applications built on streaming data through native integrations with Confluent Cloud. Through this program, Rockset is equipping Confluent customers with the tools to seamlessly integrate streaming data into real-time AI and analytics applications.
To foster further collaboration, Rockset hosted the inaugural Index Conference, an event dedicated to engineers building search, analytics, and AI applications at scale. Attendees heard speakers from JetBlue, Meta, and Uber, among others, share how they built systems that scale to millions of users, centralize search infrastructure, and serve a number of applications.
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