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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonMySQL  Xexclude from comparisonQuestDB  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 CPUsWidely used open source RDBMSA high performance open source SQL database for time series data
Primary database modelDocument storeRelational DBMSRelational DBMS infoKey/Value like access via memcached APITime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitefirebase.google.com/­products/­firestorewww.kinetica.comwww.mysql.comquestdb.io
Technical documentationfirebase.google.com/­docs/­firestoredocs.kinetica.comdev.mysql.com/­docquestdb.io/­docs
DeveloperGoogleKineticaOracle infosince 2010, originally MySQL AB, then SunQuestDB Technology Inc
Initial release2017201219952014
Current release7.1, August 20218.4.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageC, C++C and C++Java (Zero-GC), C++, Rust
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL with time-series extensions
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsuser defined functionsyes infoproprietary syntaxno
Triggersyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabrichorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication with eventual consistency
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infonot for MyISAM storage engineACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyes 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 levelUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Google Cloud FirestoreKineticaMySQLQuestDB
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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More resources
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