DBMS > AgensGraph vs. Google Cloud Datastore vs. Graph Engine vs. RDF4J vs. TimesTen

System Properties Comparison AgensGraph vs. Google Cloud Datastore vs. Graph Engine vs. RDF4J vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Graph DBMS
Relational DBMS

Document store

Graph DBMS
Key-value store

RDF store

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	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

bitnine.net/agensgraph

cloud.google.com/datastore

www.graphengine.io

rdf4j.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

bitnine.net/documentation

cloud.google.com/datastore/docs

www.graphengine.io/docs/manual

rdf4j.org/documentation

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Bitnine Global Inc.

Google

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2008

2010

2004

1998

Current release

2.1, December 2018

Release 22.1

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MIT License

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

.NET and C

Java

Server operating systems

Linux
OS X
Windows

hosted

.NET

Linux
OS X
Unix
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

depending on used data model

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

yes, details here

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 (GQL)

yes

APIs and other access methods

Cypher Query Language
JDBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
Java
JavaScript
Python

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
F#
Visual Basic

Java
PHP
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

using Google App Engine

yes

PL/SQL

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using Paxos

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Isolation support depends on the API used

ACID

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 storage is supported as well

yes

by means of logfiles and checkpoints

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 for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Graph DBMS Performance Comparison AgensGraph vs. Neo4j
29 June 2017, Business Wire

Bitnine Releases AgensGraph 2.1, the Multi-model Graph Database Optimized for the Legacy Environment
29 January 2019, Business Wire

AGE - The Open Source PostgreSQL Extension For Graph Database Functionality
27 June 2022, iProgrammer

Bitnine Global and CGI Enter $3 Million System Integrator License Agreement
5 September 2024, Yahoo Finance

Bitnine: The Newly Revealed ‘AI Teacher’ Powered by Graph Database Delivers Hyper-Personalized Learning Experience
25 March 2019, Business Wire

provided by Google News

Google Cloud vs AWS: Which Cloud Computing Platform is Better?
11 September 2024, Cloudwards

Google Gets Rid of Fees To Transfer Data Out of Cloud Platform
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
13 September 2024, TechRadar

What Is Google Cloud? Platform, Benefits & More Explained
11 September 2024, Cloudwards

Google App Engine
26 April 2024, TechTarget

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

provided by Google News

Oracle starts peddling Exalytics in-memory appliance
12 March 2012, The Register

SAP S&D Benchmark - The Intel Xeon E7-8800 v3 Review: The POWER8 Killer?
8 May 2015, AnandTech

The Intel Xeon E7-8800 v3 Review: The POWER8 Killer?
8 May 2015, AnandTech

provided by Google News

Share this page