DBMS > AgensGraph vs. Drizzle vs. GridGain vs. ToroDB

System Properties Comparison AgensGraph vs. Drizzle vs. GridGain vs. ToroDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Website

bitnine.net/agensgraph

www.gridgain.com

github.com/torodb/server

Technical documentation

bitnine.net/documentation

www.gridgain.com/docs/index.html

Developer

Bitnine Global Inc.

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

8Kdata

Initial release

2016

2008

2007

2016

Current release

2.1, December 2018

7.2.4, September 2012

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

commercial

Open Source

AGPL-V3

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++

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

with proprietary extensions

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

APIs and other access methods

Cypher Query Language
JDBC

JDBC

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

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

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

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes (replicated cache)

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

Access rights for users and roles

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