DBMS > Amazon SimpleDB vs. Microsoft Access vs. Oracle vs. Solr

System Properties Comparison Amazon SimpleDB vs. Microsoft Access vs. Oracle vs. Solr

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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

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.)

Widely used RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key-value store

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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

Score	1.88
Rank	#139	Overall
	#24	Key-value stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	44.28
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/simpledb

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

www.oracle.com/database

solr.apache.org

Technical documentation

docs.aws.amazon.com/simpledb

developer.microsoft.com/en-us/access

docs.oracle.com/en/database

solr.apache.org/resources.html

Developer

Amazon

Microsoft

Oracle

Apache Software Foundation

Initial release

2007

1992

1980

2006

Current release

1902 (16.0.11328.20222), March 2019

23c, September 2023

9.5.0, February 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

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

C++

C and C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

Supported programming languages

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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

PL/SQL

also stored procedures in Java possible

Java plugins

Triggers

yes

since Access 2010 using the ACE-engine

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual 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

ACID

but no files for transaction logging

ACID

isolation level can be parameterized

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

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

Version 12c introduced the new option 'Oracle Database In-Memory'

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

fine grained access rights according to SQL-standard

yes

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