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DBMS > Google Cloud Firestore vs. Microsoft SQL Server vs. Sphinx vs. Tkrzw vs. UniData,UniVerse

System Properties Comparison Google Cloud Firestore vs. Microsoft SQL Server vs. Sphinx vs. Tkrzw vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionCloud 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.Microsofts flagship relational DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelDocument storeRelational DBMSSearch engineKey-value storeMultivalue DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitefirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­sql-serversphinxsearch.comdbmx.net/­tkrzwwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationfirebase.google.com/­docs/­firestorelearn.microsoft.com/­en-US/­sql/­sql-serversphinxsearch.com/­docsdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperGoogleMicrosoftSphinx Technologies Inc.Mikio HirabayashiRocket Software
Initial release20171989200120201985
Current releaseSQL Server 2022, November 20223.5.1, February 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++C
Server operating systemshostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnonooptional
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesSQL-like query language (SphinxQL)noyes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Proprietary protocolJava API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanonoyes
Triggersyes, with Cloud Functionsyesnonoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding infoPartitioning is done manually, search queries against distributed index is supportednonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes, but depending on the SQL-Server EditionnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardnonoAccess rights according to SQL-standard and operating system based

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More resources
Google Cloud FirestoreMicrosoft SQL ServerSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetUniData,UniVerse
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