DBMS > AllegroGraph vs. DataFS vs. GigaSpaces vs. Google BigQuery

System Properties Comparison AllegroGraph vs. DataFS vs. GigaSpaces vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Large scale data warehouse service with append-only tables

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Object oriented DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Spatial DBMS

Graph DBMS

Graph DBMS
Search engine

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

allegrograph.com

newdatabase.com

www.gigaspaces.com

cloud.google.com/bigquery

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

dev.mobiland.com/Overview.xsp

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigquery/docs

Developer

Franz Inc.

Mobiland AG

Gigaspaces Technologies

Google

Initial release

2004

2018

2000

2010

Current release

8.0, December 2023

1.1.263, October 2022

15.5, September 2020

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

Apache Version 2; Commercial licenses available

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

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

Windows

Linux
macOS
Solaris
Windows

hosted

Data scheme

yes

RDF schemas

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

bulk load of XML files possible

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-99 for query and DML statements

yes

APIs and other access methods

RESTful HTTP API
SPARQL

.NET Client API
Proprietary client DLL
WinRT client

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

RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C#
C++
VB.Net

.Net
C++
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

user defined functions

in JavaScript

Triggers

yes

no, except callback-events from server when changes happened

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

with Federation

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

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 or Eventual Consistency depending on configuration

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Windows-Profile

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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