DBMS > Dgraph vs. Geode vs. HugeGraph vs. Postgres-XL vs. Transbase

System Properties Comparison Dgraph vs. Geode vs. HugeGraph vs. Postgres-XL vs. Transbase

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

A fast-speed and highly-scalable Graph DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

dgraph.io

geode.apache.org

github.com/hugegraph
hugegraph.apache.org

www.postgres-xl.org

www.transaction.de/en/products/transbase.html

Technical documentation

dgraph.io/docs

geode.apache.org/docs

hugegraph.apache.org/docs

www.postgres-xl.org/documentation

www.transaction.de/en/products/transbase/features.html

Developer

Dgraph Labs, Inc.

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

Baidu

Transaction Software GmbH

Initial release

2016

2002

2018

2014

since 2012, originally named StormDB

1987

Current release

1.1, February 2017

0.9

10 R1, October 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

Open Source

Mozilla public license

commercial

free development license

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 and C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Unix

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

distributed, parallel query execution

yes

APIs and other access methods

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

Java Client API
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

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

Groovy
Java
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

MVCC

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

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