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

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

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud 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 protocols
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument storeDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score7.36
Rank#53  Overall
#9  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitebigobject.iocloud.google.com/­datastorefirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdocs.bigobject.iocloud.google.com/­datastore/­docsfirebase.google.com/­docs/­firestoredocs.keydb.dev
DeveloperBigObject, Inc.GoogleGoogleEQ Alpha Technology Ltd.
Initial release2015200820172019
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedhostedLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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 indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)nono
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
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
Server-side scripts infoStored proceduresLuausing Google App Engineyes, Firebase Rules & Cloud FunctionsLua
TriggersnoCallbacks using the Google Apps Engineyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsyesOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access 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 ACL

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More resources
BigObjectGoogle Cloud DatastoreGoogle Cloud FirestoreKeyDB
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