DBMS > Amazon SimpleDB vs. BigObject vs. Microsoft Access vs. RDFox vs. SQLite

System Properties Comparison Amazon SimpleDB vs. BigObject vs. Microsoft Access vs. RDFox vs. SQLite

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

Analytic DBMS for real-time computations and queries

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

High performance knowledge graph and semantic reasoning engine

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/simpledb

bigobject.io

www.microsoft.com/en-us/microsoft-365/access

www.oxfordsemantic.tech

www.sqlite.org

Technical documentation

docs.aws.amazon.com/simpledb

docs.bigobject.io

developer.microsoft.com/en-us/access

docs.oxfordsemantic.tech

www.sqlite.org/docs.html

Developer

Amazon

BigObject, Inc.

Microsoft

Oxford Semantic Technologies

Dwayne Richard Hipp

Initial release

2007

2015

1992

2017

2000

Current release

1902 (16.0.11328.20222), March 2019

6.0, Septermber 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Bundled with Microsoft Office

commercial

Open Source

Public Domain

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

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

Not a real database server, but making use of DLLs

Linux
macOS
Windows

server-less

Data scheme

schema-free

yes

RDF schemas

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API
SPARQL 1.1

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Lua

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

replication via a shared file system

none

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

none

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

via file-system locks

Durability

Support for making data persistent

yes

but no files for transaction logging

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)

a simple user-level security was built in till version Access 2003

Roles, resources, and access types

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