DBMS > AgensGraph vs. GridGain vs. searchxml

System Properties Comparison AgensGraph vs. GridGain vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Graph DBMS
Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Native XML DBMS
Search engine

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

bitnine.net/agensgraph

www.gridgain.com

www.searchxml.net/category/products

Technical documentation

bitnine.net/documentation

www.gridgain.com/docs/index.html

www.searchxml.net/support/handouts

Developer

Bitnine Global Inc.

GridGain Systems, Inc.

informationpartners gmbh

Initial release

2016

2007

2015

Current release

2.1, December 2018

GridGain 8.5.1

1.0

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial, open source

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

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

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows
z/OS

Windows

Data scheme

depending on used data model

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

Secondary indexes

yes

SQL

Support of SQL

yes

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

APIs and other access methods

Cypher Query Language
JDBC

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
Java
JavaScript
Python

C#
C++
Java
PHP
Python
Ruby
Scala

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

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

yes

on the application server

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes

sychronisation to multiple collections

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

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Role-based access control
Security Hooks for custom implementations

Domain, group and role-based access control at the document level and for application services

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