DBMS > Riak KV vs. RRDtool vs. SingleStore

System Properties Comparison Riak KV vs. RRDtool vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

Distributed, fault tolerant key-value store

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Key-value store

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

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

oss.oetiker.ch/rrdtool

www.singlestore.com

Technical documentation

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

oss.oetiker.ch/rrdtool/doc

docs.singlestore.com

Developer

OpenSource, formerly Basho Technologies

Tobias Oetiker

SingleStore Inc.

Initial release

2009

1999

2013

Current release

3.2.0, December 2022

1.8.0, 2022

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V2 and FLOSS

commercial

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Erlang

Implementations in Java (e.g. RRD4J) and C# available

C++, Go

Server operating systems

Linux
OS X

HP-UX
Linux

Linux

64 bit version required

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

but no triggers and foreign keys

APIs and other access methods

HTTP API
Native Erlang Interface

in-process shared library
Pipes

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

User concepts

Access control

yes, using Riak Security

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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More resources

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Recent citations in the news

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22 September 2023, InformationWeek

Riak NoSQL Database: Use Cases and Best Practices
23 December 2011, InfoQ.com

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13 January 2015, Data Center Knowledge

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12 September 2017, ComputerWeekly.com

Basho distributes Riak to more customers - DCD
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