DBMS > Galaxybase vs. Graph Engine vs. GridGain

System Properties Comparison Galaxybase vs. Graph Engine vs. GridGain

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Graph DBMS

Graph DBMS
Key-value store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Website

galaxybase.com

www.graphengine.io

www.gridgain.com

Technical documentation

www.graphengine.io/docs/manual

www.gridgain.com/docs/index.html

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

GridGain Systems, Inc.

Initial release

2017

2010

2007

Current release

Nov 20, November 2021

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

MIT License

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.

Implementation language

C and Java

.NET and C

Java, C++, .Net, Python, REST, SQL

Server operating systems

Linux

.NET

Linux
OS X
Solaris
Windows
z/OS

Data scheme

Strong typed schema

yes

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

Secondary indexes

yes

SQL

Support of SQL

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

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP API

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

Supported programming languages

Go
Java
Python

C#
C++
F#
Visual Basic

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined procedures and functions

yes

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Role-based access control

Role-based access control
Security Hooks for custom implementations

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More resources

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