StarRocks, a new-generation massively parallel processing (MPP) database service designed for all analytical scenarios, launched the 2.0 version. This new version delivers a myriad of performance improvements in both single-table and multi-table query scenarios. The single-table query performance is twice that of its competitors. The multi-table query performance is five to ten times that of other database systems. StarRocks 2.0 introduces a new model, the primary key model, which enhances real-time update performance by three to ten times. In addition, the memory management scheme is redesigned in 2.0 to accommodate customers’ requirements for higher availability and stability.
Last September, StarRocks opened its source code to global communities and communities have become a key driving force behind the improvement of StarRocks. StarRocks has received more than 2,000 GitHub stars within the first 135 days after the code is open. Hundreds of large and medium-sized enterprises are attracted to use StarRocks.
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StarRocks 2.0 is ideal for single-table and multi-table queries. For single-table queries, StarRocks 2.0 innovatively uses global dictionaries to optimize queries on low-cardinality fields, delivering a single-table query performance twice that of its earlier versions and also other leading database service providers. For multi-table queries, StarRocks 2.0 has resigned the cost-based optimizer (CBO) to handle complex multi-table queries, improving multi-table query performance by two times and making StarRocks 2.0 five to ten times faster than other database systems.
In terms of data updates, traditional OLAP systems use the merge-on-read mode to update data, which is not the best solution because it pursues data loading efficiency at the cost of query performance. As real-time data update requirements keep rising in the finance and logistics sectors, this model no longer lives up to expectations. StarRocks 2.0 introduces a novel data model, the primary key model, to update data in delete-and-insert mode. This innovation enhances query performance by three to ten times in real-time update scenarios.
In addition, the memory management scheme is redesigned in StarRocks 2.0 to improve system stability. A pipeline execution engine built for higher concurrency and faster complex queries on multi-core machines has been released for trial use. This engine will be officially released in StarRocks 2.1.