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

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

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatabend  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityCloud 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 imposedRelational DBMSDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score6.63
Rank#54  Overall
#9  Document stores
Score0.63
Rank#232  Overall
#32  Key-value stores
Websitebigobject.iogithub.com/­datafuselabs/­databend
www.databend.com
firebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdocs.bigobject.iodocs.databend.comfirebase.google.com/­docs/­firestoredocs.keydb.dev
DeveloperBigObject, Inc.Databend LabsGoogleEQ Alpha Technology Ltd.
Initial release2015202120172019
Current release1.0.59, April 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache Version 2.0commercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hosted
Linux
macOS
hostedLinux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyespartial 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 indexesyesnoyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnono
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
CLI Client
JDBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
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 proceduresLuanoyes, Firebase Rules & Cloud FunctionsLua
Triggersnonoyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyesOptimistic 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.yesyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user rolesAccess 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
BigObjectDatabendGoogle Cloud FirestoreKeyDB
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