DBMS > Riak TS vs. RocksDB vs. Solr vs. Splunk vs. Tkrzw

System Properties Comparison Riak TS vs. RocksDB vs. Solr vs. Splunk vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

A widely used distributed, scalable search engine based on Apache Lucene

Analytics Platform for Big Data

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

Technical documentation

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

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

docs.splunk.com/Documentation/Splunk

Developer

Open Source, formerly Basho Technologies

Facebook, Inc.

Apache Software Foundation

Splunk Inc.

Mikio Hirabayashi

Initial release

2015

2013

2006

2003

2020

Current release

3.0.0, September 2022

9.2.1, May 2024

9.6.1, May 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache Version 2

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0

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

Erlang

C++

Java

C++

Server operating systems

Linux
OS X

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes, limited

Solr Parallel SQL Interface

Splunk Search Processing Language for search commands

APIs and other access methods

HTTP API
Native Erlang Interface

C++ API
Java API

Java API
RESTful HTTP/JSON API

HTTP REST

Supported programming languages

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
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Erlang

Java plugins

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

yes

optimistic locking

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.

yes

using specific database classes

User concepts

Access control

yes

Access rights for users and roles

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