HomeContentNewsStarRocks Presents Open Source OLAP Database To The Cloud

StarRocks Presents Open Source OLAP Database To The Cloud

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StarRocks, a provider of open source online analytical processing databases, on Thursday unveiled a beta version of its cloud database-as-a-service product. A clone of the open source Apache Doris database, which is designed for OLAP workloads, gave birth to StarRocks in the year 2020. StarRocks is currently a technology that is open source and accessible to companies for independent operation and management. With the launch of the StarRocks Cloud service, the firm has joined the two-year-old trend toward open source DBaaS platforms.

Not denormalizing

In order to optimise analytics queries, businesses don’t need to convert data from the star-schema format for database tables to what are known as denormalized tables. This is where the StarRocks database differentiates from other OLAP databases. In most cases, databases must denormalize tables in order to meet OLAP’s performance requirements. According to Kevin Petrie, an analyst at Eckerson Research, denormalization causes data to become larger, pipelines to become more complicated, and tables to update more slowly.

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“Enterprises struggle to support real-time business intelligence use cases such as reporting and dashboards,” Petrie said. “StarRocks aims to speed up queries without denormalizing tables. The hope and opportunity is to meet OLAP performance requirements in a simpler, cleaner way.”

Competitors of StarRocks include the Apache Pinot real-time indexing database, the Rockset real-time indexing database, and a cloud version from vendor StarTree. StarRocks must yet launch its cloud solution across many cloud providers. AWS is the first target, with others to follow.

How the OLAP Database is sped up using StarRocks

The vendor’s database, according to Li Kang, VP of strategy at StarRocks, does not denormalize data but has instead created a new query engine that speeds up analytics searches on star schema data. Denormalization has the drawback of making updating and removing data more difficult. According to Kang, such issue is also addressed by the real-time data access strategy of StarRocks’ data query engine.

A massively parallel processing database, which conducts several operations concurrently to support scalability and high speed, forms the basis of the StarRocks architecture. StarRocks has also created its own cost-based optimizer (CBO) for query execution in order to speed up queries even more. Based on the distribution of the data and the layout of the database tables, the CBO optimises queries.

The StarRocks Cloud will provide users two distinct deployment options when it becomes broadly accessible. Users can put StackRocks onto their own virtual private cloud using one method, which is provided as a managed service. The serverless DBaaS technique is another choice; it is sometimes mentioned in this context. In this configuration, an organisation subscribes to StarRocks as a service, and StarRocks manages all of the infrastructure resources in the cloud.

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