DBMS > Alibaba Cloud Table Store vs. atoti vs. ClickHouse vs. Ignite vs. Redis

System Properties Comparison Alibaba Cloud Table Store vs. atoti vs. ClickHouse vs. Ignite 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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Object oriented DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

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

Secondary database models

Time Series 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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.atoti.io

clickhouse.com/docs

apacheignite.readme.io/docs

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

Developer

Alibaba

ActiveViam

Clickhouse Inc.

Apache Software Foundation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2016

2015

2009

Current release

v24.4.1.2088-stable, May 2024

Apache Ignite 2.6

7.2.5, May 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

Apache 2.0

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

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

Implementation language

Java

C++

C++, Java, .Net

Server operating systems

hosted

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

Multidimensional Expressions (MDX)

Close to ANSI SQL (SQL/JSON + extensions)

ANSI-99 for query and DML statements, subset of DDL

with RediSQL module

APIs and other access methods

HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Java
PHP
Python
Ruby
Scala

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

Python

yes

yes (compute grid and cache interceptors can be used instead)

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

Triggers

yes (cache interceptors and events)

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

Sharding, horizontal partitioning

key based and custom

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

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes (replicated cache)

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

Transaction concepts

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

Atomic single-row operations

ACID

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Security Hooks for custom implementations

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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