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Kinetica Independent Benchmark Results

Kinetica continues to deliver impressive results in a recent TPC-DS benchmark of leading analytical databases. And in comparisons of time-series and spatial databases, Kinetica is unequaled in it's capabilities and performance.

What do these results show us?

Report on Spatial and Time-Series Databases

An independently designed and performed Spatial and Time Series Benchmark to help organizations evaluate database technologies suitable for IoT and sensor data workloads. This report evaluates the performance and functionality of leading cloud databases with built in geospatial, temporal, and graph capabilities

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Kinetica excels on TPC-DS

Radiant Advisors performed TPC-DS benchmarks on several high performance analytics databases in late 2022. TPC-DS is a sophisticated and comprehensive benchmark for SQL analytics databases, and an industry standard benchmark for general purpose decision support systems.

Many of the queries are long with complex joins, aggregations and group-bys. The full suite of TPC-DS SQL queries can be found on Github.

Kinetica much faster than other databases overall

Using similar hardware, Kinetica beats other high-performance databases overall.

Benchmark Summary from Benchmark Advisors

Benchmark Chart

Comparisons are made to Kinetica from a geomean of the queries the database was able to run. So Clickhouse was
13x slower overall on the 8 queries it was able to successfully complete.

vs

Kinetica is 5x faster than BigQuery

Kinetica is substantially faster than BigQuery over most queries
Tests were run with 200GB (SF200) of sample data comprising 24 tables in a snowflake schema. The tables store web, catalog and store sales from an imaginary retailer. The largest fact table had well over a billion rows. Benchmarking was done using a consistent distributed hardware configuration of four Azure virtual machines: E48s v4 (48 vCPU, 384 GB RAM) with 2TB premium SSD, or equivalent setup.

Overall Query Results

Kinetica's vectorized join algorithms surpass other high-performance databases on most queries

View the Individual TPC-DS Queries Here

What is notable from these results?

Vectorized architecture delivers performance

Kinetica's unique native vectorized join engine is able to process chunks of data in parallel, rather than sequentially working through rows of data line by line. This delivers very quick results, particularly with complex ad-hoc analysis of complex data.

Mature database capable of running complex SQL

Kinetica has been in development for over a decade. It is mature and battle-tested and able to reliably parse and deliver results on complex SQL queries. Kinetica is typically able to run all 99 queries of the TPC-DC harness.

Geospatial and time-series capabilities also included

Kinetica fast, real-time capabilities extend out to it's versatile suite of functionality for time-series and geospatial analysis, as well as graph query modes, and easy to use notebook tools for building multi-step queries.

Book a Demo!

The best way to appreciate the possibilities that Kinetica brings to high-performance real-time analytics is to see it in action.

Contact us, and we'll give you a tour of Kinetica. We can also help you get started using it with your own data, your own schemas and your own queries.