DBMS > AllegroGraph vs. Oracle vs. PouchDB vs. TigerGraph

System Properties Comparison AllegroGraph vs. Oracle vs. PouchDB vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.84
Rank	#204	Overall
	#35	Document stores
	#18	Graph DBMS
	#7	RDF stores
	#10	Vector DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

allegrograph.com

www.oracle.com/database

pouchdb.com

www.tigergraph.com

Technical documentation

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

docs.oracle.com/en/database

pouchdb.com/guides

docs.tigergraph.com

Developer

Franz Inc.

Oracle

Apache Software Foundation

Initial release

2004

1980

2012

2017

Current release

8.0, December 2023

23c, September 2023

7.1.1, June 2019

License

Commercial or Open Source

commercial

Limited community edition free

commercial

restricted free version is available

Open Source

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++

JavaScript

C++

Server operating systems

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

RDF schemas

yes

Schemaless in JSON and XML columns

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

yes

Secondary indexes

yes

via views

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

C++
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

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10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Awesome AI Companies – Franz Inc.
17 July 2024

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