DBMS > IBM Cloudant vs. Quasardb vs. Realm vs. TimescaleDB vs. TimesTen

System Properties Comparison IBM Cloudant vs. Quasardb vs. Realm vs. TimescaleDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Distributed, high-performance timeseries database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Relational DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.ibm.com/products/cloudant

quasar.ai

realm.io

www.timescale.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

cloud.ibm.com/docs/Cloudant

doc.quasar.ai/master

realm.io/docs

docs.timescale.com

docs.oracle.com/database/timesten-18.1

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

quasardb

Realm, acquired by MongoDB in May 2019

Timescale

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2009

2014

2017

1998

Current release

3.14.1, January 2024

2.15.0, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache 2.0

commercial

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++

Server operating systems

hosted

BSD
Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

runs within the applications so server-side scripts are unnecessary

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

PL/SQL

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

none

Source-replica replication with hot standby and reads on replicas

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Transient mode

yes

In-Memory realm

yes

User concepts

Access control

Access rights for users can be defined per database

Cryptographically strong user authentication and audit trail

yes

fine grained access rights according to SQL-standard

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