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DBMS > Google Cloud Firestore vs. HarperDB vs. Kinetica vs. Sphinx

System Properties Comparison Google Cloud Firestore vs. HarperDB vs. Kinetica vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  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.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Fully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.63
Rank#54  Overall
#9  Document stores
Score0.55
Rank#243  Overall
#38  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitefirebase.google.com/­products/­firestorewww.harperdb.iowww.kinetica.comsphinxsearch.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.harperdb.io/­docsdocs.kinetica.comsphinxsearch.com/­docs
DeveloperGoogleHarperDBKineticaSphinx Technologies Inc.
Initial release2017201720122001
Current release3.1, August 20217.1, August 20213.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC, C++C++
Server operating systemshostedLinux
OS X
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesno
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.nonono
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1user defined functionsno
Triggersyes, with Cloud Functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infothe nodes on which a table resides can be definedSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
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.Access rights for users and rolesAccess rights for users and roles on table levelno

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More resources
Google Cloud FirestoreHarperDBKineticaSphinx
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