DBMS > Atos Standard Common Repository vs. Google Cloud Firestore vs. InterSystems Caché vs. JaguarDB vs. Transbase

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Firestore vs. InterSystems Caché vs. JaguarDB vs. Transbase

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A multi-model DBMS and application server

Performant, highly scalable DBMS for AI and IoT applications

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Key-value store

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

firebase.google.com/products/firestore

www.intersystems.com/products/cache

www.jaguardb.com

www.transaction.de/en/products/transbase.html

Technical documentation

firebase.google.com/docs/firestore

docs.intersystems.com

www.jaguardb.com/support.html

www.transaction.de/en/products/transbase/features.html

Developer

Atos Convergence Creators

Google

InterSystems

DataJaguar, Inc.

Transaction Software GmbH

Initial release

2016

2017

1997

2015

1987

Current release

1703

2018.1.4, May 2020

3.3 July 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

free development license

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

C++

the server part. Clients available in other languages

C and C++

Server operating systems

Linux

hosted

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

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

depending on used data model

yes

Typing

predefined data types such as float or date

optional

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

LDAP

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages with LDAP bindings

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
C++
Java

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Source-replica replication

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

yes

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

LDAP bind authentication

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users, groups and roles

rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

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