DBMS > ClickHouse vs. Hive vs. Ignite vs. Postgres-XL vs. searchxml

System Properties Comparison ClickHouse vs. Hive vs. Ignite vs. Postgres-XL vs. searchxml

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

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Native XML DBMS
Search engine

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.searchxml.net/category/products

Technical documentation

clickhouse.com/docs

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

apacheignite.readme.io/docs

www.postgres-xl.org/documentation

www.searchxml.net/support/handouts

Developer

Clickhouse Inc.

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

informationpartners gmbh

Initial release

2016

2012

2015

2014

since 2012, originally named StormDB

2015

Current release

v24.4.1.2088-stable, May 2024

3.1.3, April 2022

Apache Ignite 2.6

10 R1, October 2018

1.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Mozilla public license

commercial

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

C++, Java, .Net

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
macOS

Windows

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.

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

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

yes

distributed, parallel query execution

APIs and other access methods

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

JDBC
ODBC
Thrift

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API
WebDAV
XQuery
XSLT

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
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

user defined functions

yes

on the application server

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

horizontal partitioning

none

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

yes (replicated cache)

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

multiple readers, single writer

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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