DBMS > Amazon SimpleDB vs. atoti vs. Blueflood vs. Faircom DB

System Properties Comparison Amazon SimpleDB vs. atoti vs. Blueflood vs. Faircom DB

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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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Scalable TimeSeries DBMS based on Cassandra

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

Primary database model

Key-value store

Object oriented DBMS

Time Series DBMS

Key-value 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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

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

Website

aws.amazon.com/simpledb

atoti.io

blueflood.io

www.faircom.com/products/faircom-db

Technical documentation

docs.aws.amazon.com/simpledb

docs.atoti.io

github.com/rax-maas/blueflood/wiki

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

Developer

Amazon

ActiveViam

Rackspace

FairCom Corporation

Initial release

2007

2013

1979

Current release

V12, November 2020

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

commercial

Restricted, free version 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

Java

ANSI C, C++

Server operating systems

hosted

Linux
OS X

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

easily portable to other OSs

Data scheme

schema-free

predefined scheme

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

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

Multidimensional Expressions (MDX)

yes, ANSI SQL with proprietary extensions

APIs and other access methods

RESTful HTTP API

HTTP REST

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

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

Server-side scripts

Stored procedures

Python

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding, horizontal partitioning

Sharding

based on Cassandra

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

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

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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

Recent citations in the news

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

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

Amazon Goes Back to the Future With 'NoSQL' Database
19 January 2012, WIRED

provided by Google News

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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

provided by Google News

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