DBMS > Dgraph vs. Geode vs. GigaSpaces vs. MonetDB vs. RocksDB

System Properties Comparison Dgraph vs. Geode vs. GigaSpaces vs. MonetDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A relational database management system that stores data in columns

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

Primary database model

Graph DBMS

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

dgraph.io/docs

geode.apache.org/docs

docs.gigaspaces.com/latest/landing.html

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

Dgraph Labs, Inc.

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

Gigaspaces Technologies

MonetDB BV

Facebook, Inc.

Initial release

2016

2002

2000

2004

2013

Current release

1.1, February 2017

15.5, September 2020

Dec2023 (11.49), December 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; Commercial licenses available

Open Source

Mozilla Public License 2.0

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

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

SQL-99 for query and DML statements

yes

SQL 2003 with some extensions

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C++
Java
Python
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

yes, in SQL, C, R

Triggers

yes

Cache Event Listeners

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

yes

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

Planned for future releases

Access rights per client and object definable

Role-based access control

fine grained access rights according to SQL-standard

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