DBMS > Amazon Redshift vs. Amazon SimpleDB vs. CrateDB vs. Microsoft Access

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. CrateDB vs. Microsoft Access

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Distributed Database based on Lucene

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.)

Primary database model

Relational DBMS

Key-value store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

cratedb.com

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

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

cratedb.com/docs

developer.microsoft.com/en-us/access

Developer

Amazon (based on PostgreSQL)

Amazon

Crate

Microsoft

Initial release

2012

2007

2013

1992

Current release

5.8.1, August 2024

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

commercial

Bundled with Microsoft Office

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

C++

Server operating systems

hosted

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Windows

Not a real database server, but making use of DLLs

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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

restricted

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions (Javascript)

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Configurable replication on table/partition-level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Read-after-write consistency on record level

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

rights management via user accounts

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

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