DBMS > ClickHouse vs. Cubrid vs. Geode vs. Prometheus vs. Sphinx

System Properties Comparison ClickHouse vs. Cubrid vs. Geode vs. Prometheus vs. Sphinx

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.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Open-source Time Series DBMS and monitoring system

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

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	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

clickhouse.com

cubrid.com (korean)
cubrid.org (english)

geode.apache.org

prometheus.io

sphinxsearch.com

Technical documentation

clickhouse.com/docs

cubrid.org/manuals

geode.apache.org/docs

prometheus.io/docs

sphinxsearch.com/docs

Developer

Clickhouse Inc.

CUBRID Corporation, CUBRID Foundation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Sphinx Technologies Inc.

Initial release

2016

2008

2002

2015

2001

Current release

v24.4.1.2088-stable, May 2024

11.0, January 2021

1.1, February 2017

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

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.

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Implementation language

C++

C, C++, Java

Java

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language (OQL)

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
OLE DB

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

Proprietary protocol

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Multi-source replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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.

fine grained access rights according to SQL-standard

Access rights per client and object definable

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