DBMS > ClickHouse vs. Manticore Search vs. MaxDB vs. Netezza vs. OrigoDB

System Properties Comparison ClickHouse vs. Manticore Search vs. MaxDB vs. Netezza 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.

Multi-storage database for search, including full-text search.

A robust and reliable RDBMS optimized to run all major SAP solutions

Data warehouse and analytics appliance part of IBM PureSystems

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Search engine

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

clickhouse.com

manticoresearch.com

maxdb.sap.com

www.ibm.com/products/netezza

origodb.com

Technical documentation

clickhouse.com/docs

manual.manticoresearch.com

maxdb.sap.com/documentation

origodb.com/docs

Developer

Clickhouse Inc.

Manticore Software

SAP, acquired from Software AG (Adabas-D) in 1997

IBM

Robert Friberg et al

Initial release

2016

2017

1984

2000

2009

under the name LiveDB

Current release

v24.4.2.141-stable, June 2024

6.0, February 2023

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

Limited community edition free

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++

Server operating systems

FreeBSD
Linux
macOS

FreeBSD
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

included in appliance

Linux
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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 index from XML

can be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC
OLE DB

.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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C#
Java
Perl
PHP
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

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

none

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.

Synchronous replication based on Galera library

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

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 Manticore index.

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.

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Role based authorization

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