Comparison between ApsaraDB for Redis Enhanced Edition (Tair) and ApsaraDB for Redis Community Edition - ApsaraDB for Redis

This topic compares the features of ApsaraDB for Redis Enhanced Edition (Tair) and Community Edition to help you select an instance series that meets your business requirements.

Key features and supported scenarios


Edition	Series	Feature	Scenario
ApsaraDB for Redis Enhanced Edition (Tair)	DRAM-based instances	DRAM-based instances use the multi-threading model and provide read and write performance approximately three times that of ApsaraDB for Redis Community Edition instances with the same specifications. DRAM-based instances provide multiple enhanced data structure modules such as TairString (including CAS and CAD commands), TairHash, TairGIS, TairBloom, TairDoc, TairTS, TairCpc, TairZset, TairRoaring, TairVector, and TairSearch. These instances eliminate concerns about storage structures and timeliness and allow you to focus on application development. DRAM-based instances provide high compatibility. DRAM-enhanced instances are fully compatible with open source Redis. You can switch from open source Redis to ApsaraDB for Redis without the need to modify application code. DRAM-based instances provide a variety of enterprise-grade features such as data flashback, proxy query cache, and Global Distributed Cache for Redis. For more information, see Use data flashback to restore data by point in time, Use proxy query cache to address issues caused by hotkeys, and Overview.	Performance-centric business scenarios.
	Persistent memory-optimized instances	Persistent memory-optimized instances provide ultra-high cost-effectiveness. The price of persistent memory-optimized instances is 30% lower than that of ApsaraDB for Redis Community Edition instances with the same capacity. The performance of persistent memory-optimized instances reaches 90% of that of native Redis databases. Persistent memory-optimized instances support the TairString (including CAS and CAD commands), TairHash, and TairCpc enhanced data structure modules. Persistent memory-optimized instances prevent data loss when power failures occur. These instances implement persistence for each command. The system will return a success response for each write operation only after the data is persistently stored. You can use persistent memory-optimized instances as in-memory databases instead of caches. Persistent memory-optimized instances optimize the append-only file (AOF) rewriting performance for large-sized Redis databases. These instances reduce the latency and jitters that are caused when Redis calls forks to rewrite the AOF. Persistent memory-optimized instances deliver high compatibility. These instances are compatible with most data structures and commands of native Redis databases.	Data cache and storage scenarios that require high performance and high data persistence, and can bear high costs.
	ESSD-based instances	Reduces costs. These instances reduce up to 85% of costs compared with ApsaraDB for Redis Community Edition instances. Stores data in cloud disks. These instances store data in ESSDs to ensure high data reliability. The capacity of an ESSD-based instance reaches hundreds of terabytes. For more information, see ESSDs. Optimizes memory usage for large Redis databases. These instances reduce the amount of memory that is reserved for the forks of native Redis databases. Delivers high compatibility. ESSD-based instances are compatible with most data structures and commands of native Redis databases.	Data storage scenarios that require a large capacity and low costs, involve only infrequent data access, and may cause high access latency.
ApsaraDB for Redis Community Edition	N/A	Compatible with open source Redis databases and provides high performance.	Small-sized applications, medium-sized applications, applications for verification, and standard Redis usage and data migration scenarios.

Note For more information about instance series, see Select an ApsaraDB for Redis instance.

Feature comparison

In the following table, ✔️ indicates that this feature is supported, and ❌ indicates that this feature is not supported.

Note Hybrid-storage instances are phrased out. For more information, see End-of-Sale for ApsaraDB for Redis hybrid-storage instances. We recommend that you choose Persistent memory-optimized instances.

If you have purchased a hybrid-storage instance, you can submit a ticket to migrate the data of the instance.


Category	Feature	ApsaraDB for Redis Enhanced Edition (Tair)				ApsaraDB for Redis Community Edition
Category	Feature	DRAM-based instances	Persistent memory-optimized instances	ESSD-based instances	Hybrid-storage instances (phased out)	Instances that runs Redis 2.8, 4.0, or 5.0	Instances that runs Redis 6.0
Basic performance	Performance benchmark (based on Community Edition)	300%	90%	Read: 50%	90% to 40% ②	Same	120%
	Performance benchmark (based on Community Edition)	300%	90%	Write: 30%	90% to 40% ②	Same	120%
	Maximum number of connections to each data node	30,000	10,000	10,000	10,000	10,000	10,000
	Service capability of a single key (QPS reference value) ①	450,000	130,000	60,000 to 30,000 ②	120,000 to 60,000 ②	140,000	160,000
	Maximum bandwidth (Mbit/s)	96~2048	96~2048	128~1024	48~1536	10~2048	10~2048
Specifications	Disk type	Local disks	Persistent memory	PL1 ESSDs	Local disks	Local disks	PL1 ESSDs
	Disk type	PL1 ESSDs	Persistent memory	PL1 ESSDs	Local disks	Local disks	PL1 ESSDs
	Threading model	Multiple I/O threads + single worker thread (the Real Multi-I/O model) ③	Single I/O thread + single worker thread	Multiple I/O + multiple workers (Real Multi-I/O)	Single I/O thread + multiple worker threads	Single I/O thread + single worker thread	Multiple I/O + single worker
	Cost per unit (based on Community Edition)	117%	70%	15%~20%	30%	Same	Same
Data structures	Basic data structures and supported commands	Different instances support different commands. For more information, see Limits on commands supported by ApsaraDB for Redis Enhanced Edition (Tair).				For more information about the commands that are not supported, see Commands supported by ApsaraDB for Redis Community Edition.
Data structures	Integration of multiple Redis modules	✔️	✔️️️️️ (integration with specific Redis modules)	❌	❌	❌	❌
Data persistence	Master-replica replication consistency	Eventual consistency	Eventual consistency	Eventual consistency	Eventual consistency	Eventual consistency	Eventual consistency
	Persistent data consistency ④	Write Back	Write Through	Write Through	Write Back	Write Back	Write Back
	Persistence level	Within seconds	Command-level	Command-level	Within seconds	Within seconds	Within seconds
Data security	Audit logs	✔️	❌	❌	❌	✔️	❌
	SSL encryption	✔️	❌	❌	✔️	✔️	❌
	Whitelists	✔️	✔️	✔️	✔️	✔️	✔️
Performance analysis	Use the real-time key statistics feature	✔️	✔️	✔️	❌	✔️	✔️
	Query historical hotkeys	✔️	❌	❌	❌	✔️	❌
	Real-time large key query	✔️	✔️	❌	❌	✔️ (not supported in Redis 2.8)	✔️
	Offline large key analysis	✔️	✔️	✔️	❌	✔️	✔️
Advanced features	Use data flashback to restore data by point in time	✔️	❌	❌	❌	❌	❌
	Proxy query cache	✔️	❌	❌	❌	❌	❌
	Global Distributed Cache	✔️	❌	❌	❌	❌	❌
	One-way data synchronization by using Data Transmission Service (DTS)	✔️	❌	❌	✔️	✔️	✔️
	Two-way data synchronization by using DTS	✔️	✔️	✔️	❌	❌	❌

The following section provides the description of each numeric label:

①: The queries per second (QPS) reference value is measured by a command with a time complexity of O(1). The higher the time complexity, the lower the QPS reference value.
②: This metric is related to the distribution of cold and hot data that is accessed. A higher hit rate on memory indicates that the instance provides the performance closer to that of a Community Edition instance.
③: Different from the multi-threading model of Community Edition 6.0, the Real Multi-I/O model of DRAM-based instances provides fully accelerated I/O threads to support connections and linearly increases throughput.
④: Tair uses the following methods to store data:
- Write Through: writes data directly to disks and returns a success response.
- Write Back: writes data to the cache, returns a success response, and then writes the data to disks.