DBMS > AllegroGraph vs. BaseX vs. EJDB vs. Google BigQuery vs. Sphinx

System Properties Comparison AllegroGraph vs. BaseX vs. EJDB vs. Google BigQuery vs. Sphinx

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Large scale data warehouse service with append-only tables

Open source search engine for searching in data from different sources, e.g. relational databases

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
	#8	Vector DBMS

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

allegrograph.com

basex.org

github.com/Softmotions/ejdb

cloud.google.com/bigquery

sphinxsearch.com

Technical documentation

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

docs.basex.org

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/bigquery/docs

sphinxsearch.com/docs

Developer

Franz Inc.

BaseX GmbH

Softmotions

Google

Sphinx Technologies Inc.

Initial release

2004

2007

2012

2010

2001

Current release

8.0, December 2023

11.0, June 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

BSD license

Open Source

GPLv2

commercial

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

Linux
OS X
Windows

server-less

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

RDF schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

string, integer, double, bool, date, object_id

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

full-text index on all search fields

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API
SPARQL

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

in-process shared library

RESTful HTTP/JSON API

Proprietary protocol

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

user defined functions

in JavaScript

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

multiple readers, single writer

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

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 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

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9 February 2024

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23 January 2024

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