DBMS > Kinetica vs. MonetDB vs. PouchDB vs. RocksDB vs. Splunk

System Properties Comparison Kinetica vs. MonetDB vs. PouchDB vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

A relational database management system that stores data in columns

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

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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Trend Chart

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational 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

Technical documentation

docs.kinetica.com

www.monetdb.org/Documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Kinetica

MonetDB BV

Apache Software Foundation

Facebook, Inc.

Splunk Inc.

Initial release

2012

2004

2012

2013

2003

Current release

7.1, August 2021

Dec2023 (11.49), December 2023

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

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, C++

JavaScript

C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

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

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

HTTP REST

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, in SQL, C, R

View functions in JavaScript

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Access rights for users and roles

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