DBMS > Faircom DB vs. InterSystems Caché vs. Realm vs. RethinkDB

System Properties Comparison Faircom DB vs. InterSystems Caché vs. Realm vs. RethinkDB

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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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A multi-model DBMS and application server

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Key-value store
Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Document store

Secondary database models

Document store

Spatial DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

www.faircom.com/products/faircom-db

www.intersystems.com/products/cache

realm.io

rethinkdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.intersystems.com

realm.io/docs

rethinkdb.com/docs

Developer

FairCom Corporation

InterSystems

Realm, acquired by MongoDB in May 2019

The Linux Foundation

since July 2017

Initial release

1979

1997

2014

2009

Current release

V13, July 2024

2018.1.4, May 2020

2.4.1, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

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

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

string, binary, float, bool, date, geometry

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 with proprietary extensions

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

.NET Client API
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C#
C++
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Access rights for users, groups and roles

yes

users and table-level permissions

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