This topic describes the new commands that are supported by ApsaraDB for Redis Enhanced Edition (Tair) instances. ApsaraDB for Redis Enhanced Edition (Tair) instances support the commands provided by Community Edition instances and specific new commands to help you simplify the development process and improve data processing efficiency.
New command types supported
|CAS and CAD commands||These commands are developed to enhance the functionality of Redis strings. You can use the commands to implement simple and efficient distributed locks based on Redis. For more information, see Implement high-performance distributed locks by using TairString.|
|TairString commands||A TairString is a string that consists of a key, a value, and a version number. Moreover, TairStings can be used to limit the range of results returned by the INCRBY and INCRBYFLOAT commands. These commands are used to increase or decrease the values of Redis strings. If a result is out of range, error messages are returned by these commands.|
|TairHash commands||Similar to a native Redis hash, a TairHash is a hash that supports a variety of data structures and provides high processing performance. In addition, TairHashes allow you to specify the time-to-live (TTL) and version number for a field. This helps you simplify the development process. TairHashes use the efficient active expiration algorithm to check the expiration time of fields and delete expired fields. This process does not increase the database response time.|
|TairGIS commands||A TairGIS is a data structure that uses R-tree indexes and supports APIs related to a geographic information system (GIS). Native Redis GEO commands allow you to use one-dimensional indexes to query points. TairGIS commands allow you to query points, linestrings, and polygons by using two-dimensional indexes. You can also use TairGIS commands to check the relationships between different elements, such as whether A contains B or A intersects with B.|
|TairBloom commands||A TairBloom is a Bloom filter that supports dynamic scaling and is fully compatible with RedisBloom commands. Compared with traditional methods that achieve a similar feature, TairBlooms consume less memory and maintain a stable false positive rate during scaling. You can use TairBlooms to check whether a large amount of data exists. In this case, a specific false positive rate is allowed.|
|TairDoc commands||A TairDoc is a document data structure. It supports JSON standards and is fully compatible with RedisJSON commands. TairDoc data is stored in binary trees and allows fast access to child elements.|
|TairTS commands||TairTS is a time series data structure that is developed on top of Redis modules. This data structure provides low-latency and high-concurrency in-memory read and write access, supports fast filtering and aggregate queries, and has both storage and computing power. TairTS simplifies the processing of time series data and significantly improves performance.|
TairCpc is a data structure developed based on the compressed probability counting (CPC) sketch. It allows you to perform high-performance computing on sampled data with a small amount of memory.
|TairZset commands||Native Redis Sorted Sets (ZSETs) allow you to sort elements based on score data of the DOUBLE type only in one dimension. To exceed the limit, Alibaba Cloud has developed the TairZset data structure that allows you to sort elements based on score data of the DOUBLE type from different dimensions. This data structure improves the efficiency of data processing and is also easy to use on the client side without the need to encode, decode, or encapsulate the data.|
The TairRoaring data structure is developed on top of Roaring bitmaps of Tair. TairRoaring uses two-level indexes and introduces multiple dynamic containers. TairRoaring also adopts optimization methods such as single instruction, multiple data (SIMD), vectorization, and popcount to provide less memory consumption and deliver higher computing efficiency for collections.
TairSearch is a full-text search module developed in-house based on Redis modules instead of open-sourced search engine software libraries such as Lucene. TairSearch uses query syntax that is similar to that of Elasticsearch.
- Performance-enhanced instances support all command types described in the preceding table. For more information about performance-enhanced instances, see Performance-enhanced instances.
- Persistent memory-optimized support CAS, CAD, and TairString commands. For more information about persistent memory-optimized instances, see Persistent memory-optimized instances. For more information about CAS, CAD, and TairString commands, see CAS and CAD commands and TairString commands.
In addition to the preceding commands, ApsaraDB for Redis Enhanced Edition (Tair) instances also support the commands that are provided by Community Edition instances. For more information about commands that are supported by Community Edition instances, see Commands supported by ApsaraDB for Redis Community Edition.