DBMS > Amazon Redshift vs. Informix vs. Microsoft Access vs. RavenDB

System Properties Comparison Amazon Redshift vs. Informix vs. Microsoft Access vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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.)

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	16.32
Rank	#35	Overall
	#21	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Website

aws.amazon.com/redshift

www.ibm.com/products/informix

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

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

developer.microsoft.com/en-us/access

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Microsoft

Hibernating Rhinos

Initial release

2012

1984

1992

2010

Current release

14.10.FC5, November 2020

1902 (16.0.11328.20222), March 2019

5.4, July 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Bundled with Microsoft Office

Open Source

AGPL version 3, 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

C, C++ and Java

C++

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authentication, authorization, and auditing controls

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

Authorization levels configured per client per database

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