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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparisonTDengine  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUsTime Series DBMS and big data platform
Primary database modelDocument storeDocument storeRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitefirebase.google.com/­products/­firestorewww.harperdb.iowww.kinetica.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationfirebase.google.com/­docs/­firestoredocs.harperdb.io/­docsdocs.kinetica.comdocs.tdengine.com
DeveloperGoogleHarperDBKineticaTDEngine, previously Taos Data
Initial release2017201720122019
Current release3.1, August 20217.1, August 20213.0, August 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialOpen Source infoAGPL V3, also commercial editions available
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.
Implementation languageNode.jsC, C++C
Server operating systemshostedLinux
OS X
LinuxLinux
Windows
Data schemeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like DML and DDL statementsStandard SQL with extensions for time-series applications
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
JDBC
RESTful HTTP API
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
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
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 rangeyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infothe nodes on which a table resides can be definedSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownono
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 operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
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 levelyes
More information provided by the system vendor
Google Cloud FirestoreHarperDBKineticaTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Google Cloud FirestoreHarperDBKineticaTDengine
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