Table of Contents
- Executive Summary
- Platform Summary
- Test Setup
- Test Results
- About Actian
- About William McKnight
- About Jake Dolezal
1. Executive Summary
Data-driven organizations rely on analytic databases to load, store, and analyze volumes of data at high speed to derive timely insights. At the same time, the skyrocketing volume of data in modern organizations’ information ecosystems place significant performance demands on legacy architectures. To fully harness their data to gain competitive advantage, businesses need modern, scalable architectures and high levels of performance and reliability. In addition, many companies are attracted to fully managed cloud services and their as-a-service deployment models that let companies leverage powerful data platforms without the burden of hiring staff to manage the resources and architecture in-house. With these models, users pay as they play and can stand up a fully functional analytic platform in the cloud with just a few clicks.
This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark H (TPC-H) to compare the Actian Platform, Google BigQuery, and Snowflake. The tests we ran revealed important performance characteristics of the three platforms (see Figure 1). On a 30TB TPC-H data set, Actian’s query response times were better than the competition in 20 of the 22 queries. In a test of five concurrent users, Actian was overall three times faster than Snowflake and nine times faster than BigQuery.
In terms of price performance, the Actian Data Platform produced even greater advantages when running the five concurrent user TPC-H queries. Actian proved roughly four times less expensive to operate than Snowflake, based on cost per query per hour, and 16 times less costly than BigQuery.
Figure 1. Overall Query Response Times (in seconds) Across 22 TPC-H Benchmark-Based Queries (lower is better)
The results of these tests indicate that the Actian Data Platform is a great choice for anyone looking to access large analytic data sets quickly and economically. Given the significant speed and cost advantages provided by the platform, it is also an excellent solution for organizations with large complex data sets that need to be accessed quickly and affordably.