DBMS > Postgres-XL vs. PostgreSQL vs. Riak KV vs. Splunk

System Properties Comparison Postgres-XL vs. PostgreSQL vs. Riak KV vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Distributed, fault tolerant key-value store

Analytics Platform for Big Data

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Search engine

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

www.postgres-xl.org

www.postgresql.org

www.splunk.com

Technical documentation

www.postgres-xl.org/documentation

www.postgresql.org/docs

www.tiot.jp/riak-docs/riak/kv/latest

docs.splunk.com/Documentation/Splunk

Developer

PostgreSQL Global Development Group

www.postgresql.org/developer

OpenSource, formerly Basho Technologies

Splunk Inc.

Initial release

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

2009

2003

Current release

10 R1, October 2018

16.3, May 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

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

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Implementation language

Erlang

Server operating systems

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X

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

XML type, but no XML query functionality

yes

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

standard with numerous extensions

Splunk Search Processing Language for search commands

APIs and other access methods

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

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

MVCC

ACID

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

Access rights for users and roles

More information provided by the system vendor

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