DBMS > Firebase Realtime Database vs. Newts vs. searchxml vs. Sphinx

System Properties Comparison Firebase Realtime Database vs. Newts vs. searchxml vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Time Series DBMS based on Cassandra

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Document store

Time Series DBMS

Native XML DBMS
Search engine

Search engine

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

firebase.google.com/products/realtime-database

opennms.github.io/newts

www.searchxml.net/category/products

sphinxsearch.com

Technical documentation

firebase.google.com/docs/database

github.com/OpenNMS/newts/wiki

www.searchxml.net/support/handouts

sphinxsearch.com/docs

Developer

Google

acquired by Google 2014

OpenNMS Group

informationpartners gmbh

Sphinx Technologies Inc.

Initial release

2012

2014

2015

2001

Current release

1.0

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

hosted

Linux
OS X
Windows

Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST
Java API

RESTful HTTP API
WebDAV
XQuery
XSLT

Proprietary protocol

Supported programming languages

Java
JavaScript
Objective-C

Java

C++

most other programming languages supported via APIs

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

on the application server

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

multiple readers, single writer

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.

User concepts

Access control

yes, based on authentication and database rules

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to Choose
8 March 2024, Appinventiv

Don't be like these 900+ websites and expose millions of passwords via Firebase
18 March 2024, The Register

Misconfigured Firebase instances leaked 19 million plaintext passwords
19 March 2024, BleepingComputer

Misconfigured firebase: A real-time cyber threat
18 January 2024, Atos

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose?
2 February 2024, Towards Data Science

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018
22 December 2018, WQXR Radio

Here’s Why Russia Is Cracking Down on Google
23 February 2015, TIME

The Pirate Bay was recently down for over a week due to a DDoS attack
29 October 2019, The Hacker News

provided by Google News

Share this page