DBMS > Alibaba Cloud Table Store vs. Amazon DocumentDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Redis

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DocumentDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Redis

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Wide column store

Document store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/documentdb

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

redis.com
redis.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

aws.amazon.com/documentdb/resources

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

docs.redis.com/latest/index.html
redis.io/docs

Developer

Alibaba

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2016

2019

2013

2014

2009

Current release

2.7.6, April 2024

7.2.4, January 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Server operating systems

hosted

Linux
OS X

through Homebrew

hosted

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

JSON types

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language

with RediSQL module

APIs and other access methods

HTTP API

proprietary protocol using JSON (MongoDB compatible)

HTTP API
JSON over UDP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

JavaScript

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

JavaScript

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

Atomic single-document operations

Multi-item ACID transactions with snapshot isolation within a partition

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles

simple rights management via user accounts

Access rights can be defined down to the item level

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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