DBMS > Fujitsu Enterprise Postgres vs. Sphinx vs. SQLite vs. Ultipa vs. VelocityDB

System Properties Comparison Fujitsu Enterprise Postgres vs. Sphinx vs. SQLite vs. Ultipa vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Secondary database models

Document store
Spatial DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

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

www.postgresql.fastware.com

Technical documentation

www.postgresql.fastware.com/product-manuals

sphinxsearch.com/docs

www.sqlite.org/docs.html

www.ultipa.com/document

velocitydb.com/UserGuide

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Sphinx Technologies Inc.

Dwayne Richard Hipp

Ultipa

VelocityDB Inc

Initial release

2001

2000

2019

2011

Current release

Fujitsu Enterprise Postgres 14, January 2022

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

7.x

License

Commercial or Open Source

commercial

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

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Any that supports .NET

Data scheme

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

.Net

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

user defined functions

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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