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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.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 modelDocument storeKey-value storeSearch engineKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score6.87
Rank#55  Overall
#6  Key-value stores
Score6.03
Rank#60  Overall
#6  Search engines
Score0.09
Rank#354  Overall
#51  Key-value stores
Websitefirebase.google.com/­products/­firestorehazelcast.comsphinxsearch.comdbmx.net/­tkrzw
Technical documentationfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperGoogleHazelcastSphinx Technologies Inc.Mikio Hirabayashi
Initial release2017200820012020
Current release5.3.6, November 20233.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen 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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (SphinxQL)no
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languagesGo
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
Triggersyes, with Cloud Functionsyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding 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 methodsUsing Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.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.Role-based access controlnono

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