ποΈ Catalogs, databases, and tables
StarRocks uses internal catalogs to manage internal data and uses external catalogs to access external data in data lake. The data stored in StarRocks is maintained inside an internal catalog which consists of one or more databases. A database manages various objects, including tables, materialized views, and views, to store, manage, and manipulate data. StarRocks adopts a privilege system that controls users' privileges to perform operations on objects, thereby enhancing data security.
ποΈ Table overview
Tables are units of data storage. Understanding the table structure in StarRocks and how to design an efficient table structure helps optimize data organization and enhance query efficiency. Also, compared to traditional databases, StarRocks can store complex semi-structured data such as JSON, ARRAY, in a columnar manner to improve query performance.
ποΈ Table types
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ποΈ Data distribution
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ποΈ Data compression
StarRocks supports data compression for table and index storage. Data compression not only helps save storage space, but also improves performance of I/O intensive tasks because StarRocks can read fewer pages from disk for each request. Note that extra CPU resource is required to compress and decompress the data.
ποΈ Indexes
4 items
ποΈ [Preview] Hybrid row-column storage
As an OLAP database, StarRocks originally stores data in the columnar storage, which can enhance the performance of complex queries, such as aggregate queries. Since v3.2.3, StarRocks also supports storing data in the hybrid row-column storage where data is stored in both row-by-row and column-by-column fashions. This hybrid row-column storage is well suited for various scenario such as primary key-based high-concurrency, low-latency point queries and partial column updates, while delivering efficient analytical capabilities comparable to columnar storage. Additionally, hybrid row-column storage supports prepared statements, which enhances query performance and security.