DBMS > Atos Standard Common Repository vs. Derby vs. Google Cloud Firestore vs. JaguarDB vs. searchxml

System Properties Comparison Atos Standard Common Repository vs. Derby vs. Google Cloud Firestore vs. JaguarDB vs. searchxml

Editorial information provided by DB-Engines

Name

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

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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.

Performant, highly scalable DBMS for AI and IoT applications

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Key-value store
Vector DBMS

Native XML DBMS
Search engine

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

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

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

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

db.apache.org/derby

firebase.google.com/products/firestore

www.jaguardb.com

www.searchxml.net/category/products

Technical documentation

db.apache.org/derby/manuals/index.html

firebase.google.com/docs/firestore

www.jaguardb.com/support.html

www.searchxml.net/support/handouts

Developer

Atos Convergence Creators

Apache Software Foundation

Google

DataJaguar, Inc.

informationpartners gmbh

Initial release

2016

1997

2017

2015

Current release

1703

10.17.1.0, November 2023

3.3 July 2023

1.0

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

GPL V3.0

commercial

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++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux

Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

schema-free

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

APIs and other access methods

LDAP

JDBC

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

JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages with LDAP bindings

Java

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

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

yes

on the application server

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

yes

sychronisation to multiple collections

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

ACID

yes

multiple readers, single writer

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

fine grained access rights according to SQL-standard

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

rights management via user accounts

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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