DBMS > AllegroGraph vs. BaseX vs. Geode vs. Google BigQuery vs. Microsoft Azure Table Storage

System Properties Comparison AllegroGraph vs. BaseX vs. Geode vs. Google BigQuery vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

Large scale data warehouse service with append-only tables

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

allegrograph.com

basex.org

geode.apache.org

cloud.google.com/bigquery

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

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

docs.basex.org

geode.apache.org/docs

cloud.google.com/bigquery/docs

Developer

Franz Inc.

BaseX GmbH

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

Google

Microsoft

Initial release

2004

2007

2002

2010

2012

Current release

8.0, December 2023

10.7, August 2023

1.1, February 2017

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

BSD license

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language (OQL)

yes

APIs and other access methods

RESTful HTTP API
SPARQL

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

user defined functions

in JavaScript

Triggers

yes

via events

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

multiple readers, single writer

yes, on a single node

Since BigQuery is designed for querying data

optimistic locking

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

Users with fine-grained authorization concept on 4 levels

Access rights per client and object definable

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

Google Cloud Identity & Access Management (IAM)

Access rights based on private key authentication or shared access signatures

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

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