DBMS > Datomic vs. Faircom EDGE vs. InterSystems Caché vs. SAP HANA

System Properties Comparison Datomic vs. Faircom EDGE vs. InterSystems Caché vs. SAP HANA

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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

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A multi-model DBMS and application server

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.datomic.com

www.faircom.com/products/faircom-edge

www.intersystems.com/products/cache

www.sap.com/products/hana.html

Technical documentation

docs.datomic.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.intersystems.com

help.sap.com/hana

Developer

Cognitect

FairCom Corporation

InterSystems

SAP

Initial release

2012

1979

1997

2010

Current release

1.0.7075, December 2023

V3, October 2020

2018.1.4, May 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Restricted, free version available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

ANSI C, C++

Server operating systems

All OS with a Java VM

Android
Linux

ARM, x86
Raspbian
Windows

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

Appliance or cloud-service

Data scheme

yes

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

depending on used data model

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Clojure
Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C#
C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

.Net, JavaScript, C/C++

yes

SQLScript, R

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

File partitioning

Customizable business rules for partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

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

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

yes

User concepts

Access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users, groups and roles

yes

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