Introduction to search index

Metadata

Storing and analyzing file metadata is essential when you manage large amounts of data, such as documents, media files, E-commerce orders, bank transactions, and carrier bills. A single table in Tablestore supports petabytes of storage and tens of millions of queries per second (QPS). It also supports multiple index types, such as global secondary indexes, full-text indexes, inverted indexes, and spatiotemporal indexes, to meet various online query requirements. This lets you easily implement efficient metadata management.

• Build a search system for hundreds of millions of shops based on the Tablestore search index

• Manage metadata for massive E-commerce orders based on Tablestore

• Build a query platform for massive insurance policies based on Tablestore

• Tablestore: A powerful tool for storing and querying user persona data

• Tablestore: A powerful tool for storing, querying, and analyzing traffic data

Spatial data

Multidimensional grid data is a type of scientific big data. It is widely used in earth sciences, such as meteorology, oceanography, geology, and topography, and its data volume is growing. Scientists in these fields must be able to quickly browse data and perform online queries. These queries are diverse and require low latency. Tablestore is a serverless table storage service for massive structured data. It offers massive storage capacity, supports large-scale concurrent access, and provides low-latency performance. This lets you easily resolve the storage and query performance issues associated with scientific big data.

Practical solution for massive meteorological grid data based on Tablestore

Internet of Things

A single table in Tablestore provides petabytes of data storage without requiring sharding and supports tens of millions of QPS. It can easily meet the storage requirements for time series data from IoT devices and monitoring systems. Direct SQL reads for big data analytics and efficient incremental stream reading interfaces enable easy batch analytics and real-time stream computing.

IoT metadata management based on Tablestore