DBMS > AllegroGraph vs. Badger vs. IBM Db2 vs. searchxml

System Properties Comparison AllegroGraph vs. Badger vs. IBM Db2 vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Common in IBM host environments, 2 different versions for host and Windows/Linux

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

allegrograph.com

github.com/dgraph-io/badger

www.ibm.com/products/db2

www.searchxml.net/category/products

Technical documentation

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

godoc.org/github.com/dgraph-io/badger

www.ibm.com/docs/en/db2

www.searchxml.net/support/handouts

Developer

Franz Inc.

DGraph Labs

IBM

informationpartners gmbh

Initial release

2004

2017

1983

host version

2015

Current release

8.0, December 2023

12.1, October 2016

1.0

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

commercial

free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Windows

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

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

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding

only with Windows/Unix/Linux Version

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

with separate tools (MQ, InfoSphere)

yes

sychronisation to multiple collections

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?
8 April 2024, TDWI

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Neuro-Symbolic AI: The Peak of Artificial Intelligence
16 November 2021, AiThority

The Foundation of Data Fabrics and AI: Semantic Knowledge Graphs - DataScienceCentral.com
19 May 2022, Data Science Central

Franz Releases the First Neuro-Symbolic AI Platform Merging Knowledge Graphs, Generative AI, and Vector Storage
11 December 2023, Datanami

provided by Google News

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