DBMS > GraphDB vs. Sphinx vs. SQLite vs. Ultipa vs. VelocityDB

System Properties Comparison GraphDB vs. Sphinx vs. SQLite vs. Ultipa vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

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

Widely used embeddable, in-process RDBMS

High performance Graph DBMS supporting HTAP high availability cluster deployment

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
Object oriented DBMS

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

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

graphdb.ontotext.com/documentation

sphinxsearch.com/docs

www.sqlite.org/docs.html

www.ultipa.com/document

velocitydb.com/UserGuide

Social network pages

Developer

Ontotext

Sphinx Technologies Inc.

Dwayne Richard Hipp

Ultipa

VelocityDB Inc

Initial release

2000

2001

2000

2019

2011

Current release

10.4, October 2023

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

7.x

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

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

Java

C++

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Any that supports .NET

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

.Net

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Go
Java
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

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

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

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Riding the Databricks Wave with Hybrid Knowledge Graphs
6 June 2024

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

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