DBMS > ClickHouse vs. EsgynDB vs. GeoSpock vs. JaguarDB vs. Percona Server for MongoDB

System Properties Comparison ClickHouse vs. EsgynDB vs. GeoSpock vs. JaguarDB vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial and temporal data processing engine for extreme data scale

Performant, highly scalable DBMS for AI and IoT applications

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

clickhouse.com

www.esgyn.cn

geospock.com

www.jaguardb.com

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

clickhouse.com/docs

www.jaguardb.com/support.html

docs.percona.com/percona-distribution-for-mongodb

Developer

Clickhouse Inc.

Esgyn

GeoSpock

DataJaguar, Inc.

Percona

Initial release

2016

2015

Current release

v24.4.1.2088-stable, May 2024

2.0, September 2019

3.3 July 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3.0

Open Source

GPL Version 2

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 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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

C++, Java

Java, Javascript

C++

the server part. Clients available in other languages

C++

Server operating systems

FreeBSD
Linux
macOS

Linux

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

temporal, categorical

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

ANSI SQL for query only (using Presto)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC

JDBC
ODBC

proprietary protocol using JSON

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

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes

Java Stored Procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

via In-Memory Engine

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.

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

rights management via user accounts

Access rights for users and roles

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