Run complex queries faster on petabyte-scale data
The OcientAIQ™ Unified Data Platform helps teams accelerate analytical workloads across massive data sets, concurrent users, and complex enterprise environments.
Built to find better execution paths at scale
The OcientAIQ Unified Data Platform uses indexing, machine learning, and advanced execution planning to identify efficient paths through high-volume, high-cardinality data. The result is faster queries, better resource utilization, and more predictable performance at scale.
The OcientAIQ platform can generate execution plans for queries that traditional systems may never find, helping teams analyze larger data sets, more dimensions, and more concurrent workloads without slowing down decision-making.
Instead of relying only on histograms to estimate selectivity, the OcientAIQ platform uses multi-dimensional probability density functions to build compute-cost models that identify efficient plans for each workload.
The OcientAIQ platform is designed to avoid unnecessary scans, access data across more dimensions, and isolate the records most relevant to each workload. These capabilities help teams return results in minutes or seconds instead of hours or days.
- Secondary indexes help locate and access data faster across more dimensions of analysis.
- Segment-level time values make time-based retrieval more efficient.
- Clustering keys help isolate relevant records and skip unnecessary scans.
- Indexes on complex data types help speed analysis of arrays, matrices, and other complex structures.
Dylan Murphy, Senior VP of Product at Ocient, explains how OcientAIQ uses secondary indexing to improve performance on massive-scale analytical workloads.
Ready to accelerate your most complex workloads?
See how the OcientAIQ Unified Data Platform helps teams optimize query performance, reduce response times, and put petabyte-scale data to work for analytics and AI.