Enrich your data and analytics capabilities with a platform engineered for hyperscale data analytics
The Ocient Hyperscale Data Warehouse™ enables always-on, compute-intensive analysis of large-scale time series and geospatial data, delivering massively parallel processing for real-time analytics and SQL workloads.
Whether you’re dealing with massive amounts of data, executing highly complex workloads, or looking to consolidate tools and datasets into a single high-performance solution, the Ocient Hyperscale Data Warehouse is designed to flex to suit your most pressing data analysis requirements.
When it comes to datasets that are massive, highly complex, or both, the Ocient Hyperscale Data Warehouse rises to the challenge, delivering low-latency, continuous analysis on billions to trillions of records in real time.
Ocient delivers performance across concurrent workloads and users, enabling organizations to retire legacy platforms while gaining in performance and reducing costs.
With native support for ELT and machine learning, plus a SQL-based interface that connects easily to visualization tools via JDBC, ODBC, or Python, Ocient’s hyperscale performance enables more capabilities, delivering maximum efficiency at the lowest possible cost.
Query at hyperspeed with an architecture that’s designed to scale
Ocient’s Compute Adjacent Storage Architecture™ scales linearly to store and analyze trillions of data records in seconds, enabling users to query petabytes to hundreds of petabytes of data at full resolution with no down sampling required.
By locating NVMe drives adjacent to the processor in a Compute Adjacent Storage Architecture™, Ocient is optimized to unleash hundreds of millions of parallel tasks. With 12 drives organized into a chassis, data is scanned at over 1.2 terabits per second or read with 25M 4KB random reads per second. Utilizing techniques like kernel bypass, Ocient minimizes bottlenecks and delivers tremendous response time and concurrency so users can realize more value from their data, faster.
Hear from George Kondiles, chief architect and co-founder at Ocient, about how we use innovations like the cluster of clusters and level-based topology to address the problems associated with always-on, compute-intensive data analysis.
Learn how you can deploy Ocient and get hyperscale performance from your most challenging datasets.