DBMS > IBM Db2 vs. Oracle Berkeley DB vs. Splunk vs. SQLite

System Properties Comparison IBM Db2 vs. Oracle Berkeley DB vs. Splunk vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

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

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Search engine

Relational DBMS

Secondary database models

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	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/db2

www.oracle.com/database/technologies/related/berkeleydb.html

www.splunk.com

www.sqlite.org

Technical documentation

www.ibm.com/docs/en/db2

docs.oracle.com/cd/E17076_05/html/index.html

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

Developer

IBM

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Splunk Inc.

Dwayne Richard Hipp

Initial release

1983

host version

1994

2003

2000

Current release

12.1, October 2016

18.1.40, May 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free version is available

Open Source

commercial license available

commercial

Limited free edition and free developer edition available

Open Source

Public Domain

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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

Splunk Search Processing Language for search commands

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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