Rockset, the real-time analytics database built for the cloud, announced a new release that isolates streaming ingestion from low latency queries for real-time data applications. Just like compute-storage separation was a game-changer for cloud data warehouses, compute-compute separation for real-time analytics unlocks new efficiencies in the cloud. It eliminates compute over-provisioning by allowing either streaming ingest or query serving to be scaled up and down independently. It also enables multiple isolated applications on shared real-time data, without the need for multiple replicas.
Real-time analytics has seen rapid growth with digital supply chains, e-commerce personalization, fraud detection, and real-time pricing driving both operational efficiencies and revenue growth for organizations of all sizes. One of the primary challenges in deploying real-time data applications efficiently at scale has been the compute-intensive nature of ingesting streaming data and serving low latency queries at the same time. With first-generation databases such as Elasticsearch, the lack of predictable performance arising from compute contention has led to resource over-provisioning and high operational burden for engineering teams building these applications at scale. Traditional databases rely on replicas for isolating multiple applications, but the approach requires maintaining multiple copies of the data and has proven to be too slow and expensive for real-time analytics.
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“As a cloud-native real-time analytics database, Rockset already has compute-storage separation but we found that was necessary, not sufficient for streaming architectures. Compute isolation is a critical innovation for breaking down the barriers of cost and complexity in processing high-velocity streaming data and low latency queries,” says Venkat Venkataramani, co-founder and CEO of Rockset. “Rockset is the industry’s first to extend cloud-native data architectures, delivering compute-compute separation for real-time analytics, and enabling multiple applications on shared real-time data, without any operational burden.”
“Rockset delivered true real-time ingestion and queries with sub-50 millisecond end-to-end latency, that didn’t just match Elasticsearch, but did so at much lower operational effort and cost, while handling a much higher volume and variety of data,” said Emmanuel Fuentes, head of machine learning and data platforms at Whatnot in a recent blog.
The new release with compute-compute separation is available today. It delivers key innovations including:
- Isolation of streaming ingestion and low latency queries for predictable performance without over-provisioning compute.
- Multiple applications on the same real-time data, eliminating the need for replicas.
- Fast concurrency scaling, for serving customer-facing analytics with thousands of queries per second.
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