DBMS > Citus vs. gStore vs. Lovefield vs. Oracle Coherence

System Properties Comparison Citus vs. gStore vs. Lovefield vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A native Graph DBMS to store and maintain very large RDF datasets.

Embeddable relational database for web apps written in pure JavaScript

Oracles in-memory data grid solution

Primary database model

Secondary database models

Document store

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Trend Chart

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

www.citusdata.com

en.gstore.cn

google.github.io/lovefield

www.oracle.com/java/coherence

Technical documentation

docs.citusdata.com

en.gstore.cn/#/enDocs

github.com/google/lovefield/blob/master/docs/spec_index.md

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

Developer

Google

Oracle

Initial release

2010

2016

2014

2007

Current release

8.1, December 2018

1.2, November 2023

2.1.12, February 2017

14.1, August 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

BSD

Open Source

Apache 2.0

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.

Implementation language

C++

JavaScript

Java

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

All OS with a Java VM

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

HTTP API
SPARQL 1.1

JCache
JPA
RESTful HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
PHP
Python

JavaScript

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Using read-only observers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions, Role-Based Access Control (RBAC) supported

authentification to access the cache via certificates or http basic authentication

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