DBMS > CouchDB vs. GigaSpaces vs. LeanXcale vs. MySQL vs. openGemini

System Properties Comparison CouchDB vs. GigaSpaces vs. LeanXcale vs. MySQL vs. openGemini

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Widely used open source RDBMS

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Website

www.opengemini.org
github.com/openGemini

Technical documentation

docs.couchdb.org/en/stable

docs.gigaspaces.com/latest/landing.html

dev.mysql.com/doc

docs.opengemini.org/guide

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Gigaspaces Technologies

LeanXcale

Oracle

since 2010, originally MySQL AB, then Sun

Huawei and openGemini community

Initial release

2005

2000

2015

1995

2022

Current release

3.3.3, December 2023

15.5, September 2020

8.4.0, April 2024

1.1, July 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Erlang

Java, C++, .Net

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

through Apache Derby

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
C++
Java
Python
Scala

C
Java
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a single document possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

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 can be defined per database

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

Administrators and common users accounts

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