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DBMS > DataFS vs. Google Cloud Firestore vs. Hazelcast vs. Sphinx vs. Tkrzw

System Properties Comparison DataFS vs. Google Cloud Firestore vs. Hazelcast vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.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.A widely adopted in-memory data gridOpen 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 Cabinet
Primary database modelObject oriented DBMSDocument storeKey-value storeSearch engineKey-value store
Secondary database modelsGraph DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitenewdatabase.comfirebase.google.com/­products/­firestorehazelcast.comsphinxsearch.comdbmx.net/­tkrzw
Technical documentationdev.mobiland.com/­Overview.xspfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperMobiland AGGoogleHazelcastSphinx Technologies Inc.Mikio Hirabayashi
Initial release20182017200820012020
Current release1.1.263, October 20225.3.6, November 20233.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsWindowshostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query languageSQL-like query language (SphinxQL)no
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C#
C++
VB.Net
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor Servicesnono
Triggersno, except callback-events from server when changes happenedyes, with Cloud Functionsyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access controlnono

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More resources
DataFSGoogle Cloud FirestoreHazelcastSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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