DBMS > ClickHouse vs. Hive vs. MonetDB vs. Oracle Coherence vs. OrigoDB

System Properties Comparison ClickHouse vs. Hive vs. MonetDB vs. Oracle Coherence vs. OrigoDB

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A relational database management system that stores data in columns

Oracles in-memory data grid solution

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Key-value store

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

clickhouse.com

hive.apache.org

www.monetdb.org

www.oracle.com/java/coherence

origodb.com

Technical documentation

clickhouse.com/docs

cwiki.apache.org/confluence/display/Hive/Home

www.monetdb.org/Documentation

docs.oracle.com/en/middleware/standalone/coherence

origodb.com/docs

Developer

Clickhouse Inc.

Apache Software Foundation

initially developed by Facebook

MonetDB BV

Oracle

Robert Friberg et al

Initial release

2016

2012

2004

2007

2009

under the name LiveDB

Current release

v24.4.1.2088-stable, May 2024

3.1.3, April 2022

Dec2023 (11.49), December 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

Mozilla Public License 2.0

commercial

Open Source

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++

Java

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

APIs and other access methods

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

JDBC
ODBC
Thrift

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JCache
JPA
RESTful HTTP API

.NET Client API
HTTP API
LINQ

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++
Java
PHP
Python

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

.Net
C++
Java

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in SQL, C, R

yes

Triggers

yes

Live Events

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Sharding via remote tables

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

Source-replica replication available in experimental status

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

Write ahead log

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.

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

Role based authorization

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