DBMS > GBase vs. IBM Db2 warehouse vs. Manticore Search vs. Percona Server for MongoDB vs. Riak KV

System Properties Comparison GBase vs. IBM Db2 warehouse vs. Manticore Search vs. Percona Server for MongoDB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Cloud-based data warehousing service

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

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

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.gbase.cn

www.ibm.com/products/db2/warehouse

manticoresearch.com

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

Technical documentation

manual.manticoresearch.com

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

General Data Technology Co., Ltd.

IBM

Manticore Software

Percona

OpenSource, formerly Basho Technologies

Initial release

2004

2014

2017

2015

2009

Current release

GBase 8a, GBase 8s, GBase 8c

6.0, February 2023

3.4.10-2.10, November 2017

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL Version 2

Open Source

Apache version 2, commercial enterprise edition

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.

Implementation language

C, Java, Python

C++

Erlang

Server operating systems

Linux

hosted

FreeBSD
Linux
macOS
Windows

Linux

Linux
OS X

Data scheme

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

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

Import/export of XML data possible

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

restricted

SQL

Support of SQL

Standard with numerous extensions

yes

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

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

proprietary protocol using JSON

HTTP API
Native Erlang Interface

Supported programming languages

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

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

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

PL/SQL, SQL PL

user defined functions

JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

Source-replica replication

selectable replication factor

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
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

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

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

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

yes, using Riak Security

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