DBMS > Amazon Redshift vs. Riak KV vs. Splunk vs. SQLite vs. Transbase

System Properties Comparison Amazon Redshift vs. Riak KV vs. Splunk vs. SQLite vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Distributed, fault tolerant key-value store

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store

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

Search engine

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	93.02
Rank	#13	Overall
	#2	Search engines

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

aws.amazon.com/redshift

www.splunk.com

www.sqlite.org

www.transaction.de/en/products/transbase.html

Technical documentation

docs.aws.amazon.com/redshift

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

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

www.transaction.de/en/products/transbase/features.html

Developer

Amazon (based on PostgreSQL)

OpenSource, formerly Basho Technologies

Splunk Inc.

Dwayne Richard Hipp

Transaction Software GmbH

Initial release

2012

2009

2003

2000

1987

Current release

3.2.0, December 2022

3.46.1 (13 August 2024), August 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Limited free edition and free developer edition available

Open Source

Public Domain

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C and C++

Server operating systems

hosted

Linux
OS X

Linux
OS X
Solaris
Windows

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Splunk Search Processing Language for search commands

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

none

Source-replica 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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between data sets can be stored

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

yes

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

Access rights for users and roles

fine grained access rights according to SQL-standard

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