DBMS > Amazon SimpleDB vs. IBM Cloudant vs. OpenQM vs. TerminusDB vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. IBM Cloudant vs. OpenQM vs. TerminusDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Database as a Service offering based on Apache CouchDB

QpenQM is a high-performance, self-tuning, multi-value DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Primary database model

Secondary database models

Document store
RDF store

Relational DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/simpledb

www.ibm.com/products/cloudant

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

terminusdb.com

www.timescale.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.ibm.com/docs/Cloudant

terminusdb.github.io/terminusdb/#

docs.timescale.com

Developer

Amazon

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Rocket Software, originally Martin Phillips

DataChemist Ltd.

Timescale

Initial release

2007

2010

1993

2018

2017

Current release

3.4-12

11.0.0, January 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

Open Source

Apache 2.0

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

Prolog, Rust

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

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

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

All columns are indexed automatically

yes

SQL

Support of SQL

SQL-like query language (WOQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

yes

Graph Partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Journaling Streams

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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

in-memory journaling

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users can be defined per database

Access rights can be defined down to the item level

Role-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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7 February 2017, Matthias Gelbmann

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3 August 2015, Matthias Gelbmann

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Recent citations in the news

A Place for Everything – Amazon SimpleDB
14 December 2007, AWS Blog

Hands-on Tutorial for Getting Started with Amazon SimpleDB
28 May 2010, Packt Hub

Amazon DynamoDB Serves Trillions Of Requests Per Month While Counterpart SimpleDB Is No Longer A Listed ...
12 November 2013, TechCrunch

Amazon SimpleDB Management in Eclipse
22 July 2009, AWS Blog

An Overview of Amazon Web Services - Cloud Application Architectures [Book]
22 September 2018, oreilly.com

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18 March 2019, ibm.com

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1 December 2014, Linux.com

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26 September 2019, EnterpriseAI

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22 March 2014, App Developer Magazine

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16 August 2021, ibm.com

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16 March 2021, VentureBeat

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Dublin-based data collaboration tool TerminusDB raises €3.6 million in seed round
15 March 2021, Tech.eu

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12 April 2022, United Nations Office for Disaster Risk Reduction

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

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TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

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4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

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