DBMS > Amazon Redshift vs. Datomic vs. Microsoft Access vs. RethinkDB vs. WakandaDB

System Properties Comparison Amazon Redshift vs. Datomic vs. Microsoft Access vs. RethinkDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.)

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

aws.amazon.com/redshift

www.datomic.com

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

rethinkdb.com

wakanda.github.io

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

developer.microsoft.com/en-us/access

rethinkdb.com/docs

wakanda.github.io/doc

Developer

Amazon (based on PostgreSQL)

Cognitect

Microsoft

The Linux Foundation

since July 2017

Wakanda SAS

Initial release

2012

1992

2009

2012

Current release

1.0.6735, June 2023

1902 (16.0.11328.20222), March 2019

2.4.1, August 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license 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, Clojure

C++

C++, JavaScript

Server operating systems

hosted

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

yes

since Access 2010 using the ACE-engine

yes

Triggers

By using transaction functions

yes

since Access 2010 using the ACE-engine

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

but no files for transaction logging

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

users and table-level permissions

yes

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