DBMS > Amazon SimpleDB vs. Faircom DB vs. OpenTSDB vs. RethinkDB

System Properties Comparison Amazon SimpleDB vs. Faircom DB vs. OpenTSDB vs. RethinkDB

Please select another system to include it in the comparison.

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Scalable Time Series DBMS based on HBase

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

aws.amazon.com/simpledb

www.faircom.com/products/faircom-db

opentsdb.net

rethinkdb.com

Technical documentation

docs.aws.amazon.com/simpledb

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

opentsdb.net/docs/build/html/index.html

rethinkdb.com/docs

Developer

Amazon

FairCom Corporation

currently maintained by Yahoo and other contributors

The Linux Foundation

since July 2017

Initial release

2007

1979

2011

2009

Current release

V12, November 2020

2.4.1, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

LGPL

Open Source

Apache Version 2

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

ANSI C, C++

Java

C++

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

numeric data for metrics, strings for tags

yes

string, binary, float, bool, date, geometry

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.

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API
Telnet API

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Erlang
Go
Java
Python
R
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

based on HBase

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

based on HBase

Source-replica replication

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
Tunable consistency per server, database, table, and transaction

Immediate Consistency

based on HBase

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

tunable from ACID to Eventually Consistent

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

yes

users and table-level permissions

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

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

show all

Meet some database management systems you are likely to hear more about in the future
4 August 2014, Paul Andlinger

show all

Recent citations in the news

New SimpleDB Goodies: Enhanced Select, Larger Result Sets, Mandatory HTTPS | Amazon Web Services
20 May 2009, 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

Farewell EC2-Classic, it's been swell
1 September 2023, All Things Distributed

Amazon SimpleDB Management in Eclipse | AWS News Blog
22 July 2009, AWS Blog

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

A real-time processing revival – O'Reilly
1 April 2015, O'Reilly Media

provided by Google News

How to Use RethinkDB with Node.js Applications — SitePoint
16 December 2015, SitePoint

Stripe acquires team behind NoSQL database startup RethinkDB
5 October 2016, VentureBeat

MongoDB: The Popular Database for IoT
15 August 2023, Open Source For You

RethinkDB is dead, and MongoDB isn't what killed it
24 January 2017, TechRepublic

How to deploy RethinkDB using Docker
14 February 2018, Packt Hub

provided by Google News

Share this page