DBMS > Amazon Redshift vs. FatDB vs. Google Cloud Datastore vs. InterSystems IRIS vs. MaxDB

System Properties Comparison Amazon Redshift vs. FatDB vs. Google Cloud Datastore vs. InterSystems IRIS vs. MaxDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Website

aws.amazon.com/redshift

cloud.google.com/datastore

www.intersystems.com/products/intersystems-iris

maxdb.sap.com

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/datastore/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

maxdb.sap.com/documentation

Developer

Amazon (based on PostgreSQL)

FatCloud

Google

InterSystems

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2012

2008

2018

1984

Current release

2023.3, June 2023

7.9.10.12, February 2024

License

Commercial or Open Source

commercial

Limited community edition free

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

Windows

hosted

AIX
Linux
macOS
Ubuntu
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

depending on used data model

yes

Typing

predefined data types such as float or date

yes

yes, details here

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.

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Via inetgration in SQL Server

SQL-like query language (GQL)

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

using Google App Engine

yes

Triggers

yes

via applications

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication using Paxos

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Can implement custom security layer via applications

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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