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DBMS > BigObject vs. Google Cloud Firestore vs. KeyDB vs. PlanetScale

System Properties Comparison BigObject vs. Google Cloud Firestore vs. KeyDB vs. PlanetScale

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesCloud 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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument storeKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score1.49
Rank#155  Overall
#72  Relational DBMS
Websitebigobject.iofirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
planetscale.com
Technical documentationdocs.bigobject.iofirebase.google.com/­docs/­firestoredocs.keydb.devplanetscale.com/­docs
DeveloperBigObject, Inc.GoogleEQ Alpha Technology Ltd.PlanetScale
Initial release2015201720192020
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinuxDocker
Linux
macOS
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infowith proprietary extensions
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresLuayes, Firebase Rules & Cloud FunctionsLuayes infoproprietary syntax
Triggersnoyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesOptimistic locking, atomic execution of commands blocks and scriptsACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.simple password-based access control and ACLUsers with fine-grained authorization concept infono user groups or roles

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More resources
BigObjectGoogle Cloud FirestoreKeyDBPlanetScale
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