DBMS > Amazon DocumentDB vs. Amazon SimpleDB vs. Faircom DB vs. Infobright vs. Linter

System Properties Comparison Amazon DocumentDB vs. Amazon SimpleDB vs. Faircom DB vs. Infobright vs. Linter

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

RDBMS for high security requirements

Primary database model

Document store

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

aws.amazon.com/documentdb

aws.amazon.com/simpledb

www.faircom.com/products/faircom-db

ignitetech.com/softwarelibrary/infobrightdb

linter.ru

Technical documentation

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/simpledb

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

Developer

Amazon

FairCom Corporation

Ignite Technologies Inc.; formerly InfoBright Inc.

relex.ru

Initial release

2019

2007

1979

2005

1990

Current release

V12, November 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

ANSI C, C++

C and 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

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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.

Secondary indexes

yes

All columns are indexed automatically

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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).

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

Concurrent data updates can be detected by the application

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

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