DBMS > Postgres-XL vs. Sphinx vs. Splunk vs. SQLite vs. VelocityDB

System Properties Comparison Postgres-XL vs. Sphinx vs. Splunk vs. SQLite vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

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

Primary database model

Relational DBMS

Search engine

Relational DBMS

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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

Technical documentation

www.postgres-xl.org/documentation

sphinxsearch.com/docs

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

velocitydb.com/UserGuide

Developer

Sphinx Technologies Inc.

Splunk Inc.

Dwayne Richard Hipp

VelocityDB Inc

Initial release

2014

since 2012, originally named StormDB

2001

2003

2000

2011

Current release

10 R1, October 2018

3.5.1, February 2023

3.45.3 (15 April 2024), April 2024

7.x

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

GPL version 2, commercial licence available

commercial

Limited free edition and free developer edition 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
macOS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
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.

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

distributed, parallel query execution

SQL-like query language (SphinxQL)

Splunk Search Processing Language for search commands

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

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java
JavaScript
PHP
Python
Ruby

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

.Net

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

fine grained access rights according to SQL-standard

Access rights for users and roles

Based on Windows Authentication

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