DBMS > AgensGraph vs. Geode vs. Graph Engine vs. RocksDB

System Properties Comparison AgensGraph vs. Geode vs. Graph Engine vs. RocksDB

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Graph DBMS
Relational DBMS

Key-value store

Graph DBMS
Key-value store

Key-value store

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

bitnine.net/agensgraph

geode.apache.org

www.graphengine.io

rocksdb.org

Technical documentation

bitnine.net/documentation

geode.apache.org/docs

www.graphengine.io/docs/manual

github.com/facebook/rocksdb/wiki

Developer

Bitnine Global Inc.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Facebook, Inc.

Initial release

2016

2002

2010

2013

Current release

2.1, December 2018

1.1, February 2017

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

MIT License

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

.NET and C

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

.NET

Linux

Data scheme

depending on used data model

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

Cypher Query Language
JDBC

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP API

C++ API
Java API

Supported programming languages

C
Java
JavaScript
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

C#
C++
F#
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

yes

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

fine grained access rights according to SQL-standard

Access rights per client and object definable

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