DBMS > BoltDB vs. Oracle Berkeley DB vs. PouchDB vs. RocksDB vs. Splunk

System Properties Comparison BoltDB vs. Oracle Berkeley DB vs. PouchDB vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Widely used in-process key-value store

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Key-value store

Search engine

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

github.com/boltdb/bolt

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

pouchdb.com

rocksdb.org

www.splunk.com

Technical documentation

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

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation

Facebook, Inc.

Splunk Inc.

Initial release

2013

1994

2012

2013

2003

Current release

18.1.40, May 2020

7.1.1, June 2019

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

commercial license available

Open Source

BSD

commercial

Limited free edition and free developer edition available

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

JavaScript

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

Linux

Linux
OS X
Solaris
Windows

Data scheme

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.

yes

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

Splunk Search Processing Language for search commands

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

HTTP REST

Supported programming languages

.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

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

yes

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

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

User concepts

Access control

Access rights for users and roles

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