Lindorm uses LindormStore to decouple storage from computing. The storage fee is separately charged. You can scale up storage resources without downtime. The storage capacity of a Lindorm instance is shared among multiple engines within the same instance.
Lindorm provides three storage types: capacity-optimized, standard, and performance-optimized. The following table describes the storage types and the scenarios in which the storage types are suitable.
|Storage type||Latency||Scenario||Recommended engine|
|Capacity-optimized||15ms ~ 3s||Suitable for scenarios in which infrequently accessed data is stored. For example,
you can use this storage type to store monitoring logs and historical orders, archive
audio and video files, store data to data lakes, and compute data offline.
Note Capacity-optimized storage uses high-density disk arrays to provide highly cost-effective storage services and support high read/write throughput. However, it delivers relatively poor random read performance. Capacity-optimized storage is suitable for the scenarios in which a large number of write requests and a small number of read requests are processed or big data analytics scenarios.
|The wide table engine, the time series engine, and the file engine|
|Standard||3ms ~ 5ms||Suitable for scenarios in which data needs to be accessed in real time. For example, you can use this storage type for feed storage, data exchanges in chats, real-time report processing, and online computing.||The wide table engine, the time series engine, the search engine, and the file engine|
|Performance-optimized||0.2ms ~ 0.5ms||Suitable for scenarios in which data access requires low latency. For example, you can use this storage type for bid advertising, user persona creation, customer group selection, real-time searches, and risk management.||The wide table engine, the time series engine, the search engine, and the file engine|