DBMS > AgensGraph vs. Amazon Neptune vs. OpenEdge vs. TigerGraph vs. VoltDB

System Properties Comparison AgensGraph vs. Amazon Neptune vs. OpenEdge vs. TigerGraph vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Fast, reliable graph database built for the cloud

Application development environment with integrated database management system

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
Relational DBMS

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	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/neptune

www.progress.com/openedge

www.tigergraph.com

www.voltdb.com

Technical documentation

bitnine.net/documentation

aws.amazon.com/neptune/developer-resources

documentation.progress.com/output/ua/OpenEdge_latest

docs.tigergraph.com

docs.voltdb.com

Developer

Bitnine Global Inc.

Amazon

Progress Software Corporation

VoltDB Inc.

Initial release

2016

2017

1984

2017

2010

Current release

2.1, December 2018

OpenEdge 12.2, March 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

depending on used data model

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (GSQL)

yes

only a subset of SQL 99

APIs and other access methods

Cypher Query Language
JDBC

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Progress proprietary ABL (Advanced Business Language)

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users and groups

Role-based access control

Users and roles with access to stored procedures

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More resources

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