DBMS > Atos Standard Common Repository vs. Google Cloud Firestore vs. Sphinx

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Firestore vs. Sphinx

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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

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.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Key-value store

Document store

Search engine

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

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

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

firebase.google.com/products/firestore

sphinxsearch.com

Technical documentation

firebase.google.com/docs/firestore

sphinxsearch.com/docs

Developer

Atos Convergence Creators

Google

Sphinx Technologies Inc.

Initial release

2016

2017

2001

Current release

1703

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

Linux

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

LDAP

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

Proprietary protocol

Supported programming languages

All languages with LDAP bindings

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

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

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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.

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More resources

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