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DBMS > Google Cloud Firestore vs. KeyDB vs. Memcached vs. Teradata Aster

System Properties Comparison Google Cloud Firestore vs. KeyDB vs. Memcached vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKeyDB  Xexclude from comparisonMemcached  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsIn-memory key-value store, originally intended for cachingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeKey-value storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score18.08
Rank#32  Overall
#4  Key-value stores
Websitefirebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
www.memcached.org
Technical documentationfirebase.google.com/­docs/­firestoredocs.keydb.devgithub.com/­memcached/­memcached/­wiki
DeveloperGoogleEQ Alpha Technology Ltd.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalTeradata
Initial release2017201920032005
Current release1.6.27, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoBSD licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
Data schemeschema-freeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnoyes
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.nonoyes infoin Aster File Store
Secondary indexesyesyes infoby using the Redis Search modulenoyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocolADO.NET
JDBC
ODBC
OLE DB
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
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsLuanoR packages
Triggersyes, with Cloud Functionsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
none infoRepcached, a Memcached patch, provides this functionallityyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesOptimistic locking, atomic execution of commands blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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.simple password-based access control and ACLyes infousing SASL (Simple Authentication and Security Layer) protocolfine grained access rights according to SQL-standard

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More resources
Google Cloud FirestoreKeyDBMemcachedTeradata Aster
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