DBMS > Firebase Realtime Database vs. Microsoft SQL Server vs. Solr vs. Tibero

System Properties Comparison Firebase Realtime Database vs. Microsoft SQL Server vs. Solr vs. Tibero

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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.

Microsofts flagship relational DBMS

A widely used distributed, scalable search engine based on Apache Lucene

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.microsoft.com/en-us/sql-server

solr.apache.org

us.tmaxsoft.com/products/tibero

Technical documentation

firebase.google.com/docs/database

learn.microsoft.com/en-US/sql/sql-server

solr.apache.org/resources.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Google

acquired by Google 2014

Microsoft

Apache Software Foundation

TmaxSoft

Initial release

2012

1989

2006

2003

Current release

SQL Server 2022, November 2022

9.6.1, May 2024

6, April 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C and Assembler

Server operating systems

hosted

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java plugins

Persistent Stored Procedure (PSM)

Triggers

Callbacks are triggered when data changes

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

optimistic locking

ACID

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

planned for next version

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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