DBMS > Amazon Redshift vs. DataFS vs. Datomic vs. InterSystems Caché vs. NSDb

System Properties Comparison Amazon Redshift vs. DataFS vs. Datomic vs. InterSystems Caché vs. NSDb

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

A multi-model DBMS and application server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/redshift

newdatabase.com

www.datomic.com

www.intersystems.com/products/cache

nsdb.io

Technical documentation

docs.aws.amazon.com/redshift

dev.mobiland.com/Overview.xsp

docs.datomic.com

docs.intersystems.com

nsdb.io/Architecture

Developer

Amazon (based on PostgreSQL)

Mobiland AG

Cognitect

InterSystems

Initial release

2012

2018

2012

1997

2017

Current release

1.1.263, October 2022

1.0.6735, June 2023

2018.1.4, May 2020

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

hosted

Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

depending on used data model

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
VB.Net

Clojure
Java

C#
C++
Java

Java
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

yes

Triggers

no, except callback-events from server when changes happened

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

Using Apache Lucene

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Windows-Profile

Access rights for users, groups and roles

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