DBMS > EXASOL vs. IBM Cloudant vs. RRDtool vs. STSdb

System Properties Comparison EXASOL vs. IBM Cloudant vs. RRDtool vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Database as a Service offering based on Apache CouchDB

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.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

www.exasol.com

www.ibm.com/products/cloudant

oss.oetiker.ch/rrdtool

github.com/STSSoft/STSdb4

Technical documentation

www.exasol.com/resources

cloud.ibm.com/docs/Cloudant

oss.oetiker.ch/rrdtool/doc

Developer

Exasol

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Tobias Oetiker

STS Soft SC

Initial release

2000

2010

1999

2011

Current release

1.8.0, 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

Open Source

GPLv2, commercial license available

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

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

Server operating systems

hosted

HP-UX
Linux

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

primitive types and user defined types (classes)

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

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

in-process shared library
Pipes

.NET Client API

Supported programming languages

Java
Lua
Python
R

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C#
Java

Server-side scripts

Stored procedures

user defined functions

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

by using the rrdcached daemon

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

Access rights for users, groups and roles according to SQL-standard

Access rights for users can be defined per database

More information provided by the system vendor

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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