DBMS > ClickHouse vs. Ignite vs. PouchDB vs. RethinkDB vs. XTDB

System Properties Comparison ClickHouse vs. Ignite vs. PouchDB vs. RethinkDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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.

JavaScript DBMS with an API inspired by CouchDB

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

clickhouse.com/docs

apacheignite.readme.io/docs

pouchdb.com/guides

rethinkdb.com/docs

www.xtdb.com/docs

Developer

Clickhouse Inc.

Apache Software Foundation

The Linux Foundation

since July 2017

Juxt Ltd.

Initial release

2016

2015

2012

2009

2019

Current release

v24.4.1.2088-stable, May 2024

Apache Ignite 2.6

7.1.1, June 2019

2.4.1, August 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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.

Implementation language

C++

C++, Java, .Net

JavaScript

C++

Clojure

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes, extensible-data-notation format

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

via views

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

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

limited SQL, making use of Apache Calcite

APIs and other access methods

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST
JDBC

Supported programming languages

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

JavaScript

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Clojure
Java

Server-side scripts

Stored procedures

yes

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

View functions in JavaScript

Triggers

yes (cache interceptors and events)

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes (replicated cache)

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 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

yes

users and table-level permissions

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