5 Key Takeaways from Load Test Analysis
- Introduction to Cube Cloud: During the webinar, Rory Gatto, a Customer Experience Engineer at Cube, introduced the concept of Cube Cloud. It is identified as a universal semantic layer assisting in various aspects like data modeling, access control, caching, and connecting multiple data sources with front-end Business Intelligence tools.
- Need for Efficient Data Serving: Lead Solutions Architect at Cube, Paco Valdez, shed light on the struggles of data warehousing and emphasized low latency and efficient data serving. Paco detailed Cube's multilayered caching system, including aspects such as memory caching and precalculations involving Cube Store.
- Objectives of Load Testing: The webinar also featured a comprehensive discussion on load testing objectives. These objectives essentially revolved around determining the query performance metrics and contrasting them with a typical data warehouse. The comprehensive range of test scenarios planned for the evaluation included a naive test with identical queries, a realistic test incorporating varied filters, and a complex test with diverse parameters.
- Performance Analysis of Cube and Traditional Data Warehouses: The first test, which sought to compare the performance of an in-memory cache, showed no discernable difference between Cube and a traditional data warehouse. However, it was in the escalated scenarios where Cube demonstrated significant predominance. Where queries were subject to random filters, Cube's pre-created caching system provided a notable performance advantage. Moreover, when random dates were factored in, Cube significantly outperformed traditional warehouses, spotlighting a tenfold improvement in request quantity and a much more substantial request per second rate.
- Benefits and Limitations of Cubestore: Paco Valdez also shifted the focus towards Qubestore's unique attributes. Designed specifically to cater to these types of queries, Qubestore boasted a purpose-built engine that offered superior performance. However, a particular query limit exists when it comes to cache inquiries. The frequency at which cache was cleared along with the use of Redis servers in the overall setup was also discussed. This helped attendees get a more nuanced understanding of both the strengths and limitations of Cube Store.