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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonQuestDB  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.Fully vectorized database across both GPUs and CPUsA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitefirebase.google.com/­products/­firestorewww.kinetica.comquestdb.iosphinxsearch.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.kinetica.comquestdb.io/­docssphinxsearch.com/­docs
DeveloperGoogleKineticaQuestDB Technology IncSphinx Technologies Inc.
Initial release2017201220142001
Current release7.1, August 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open 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 languageC, C++Java (Zero-GC), C++, RustC++
Server operating systemshostedLinuxLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsuser defined functionsnono
Triggersyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yes infoGPU vRAM or System RAMyes infothrough memory mapped files
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 roles on table levelno
More information provided by the system vendor
Google Cloud FirestoreKineticaQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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