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DBMS > Google Cloud Datastore vs. KeyDB vs. RDFox vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. KeyDB vs. RDFox vs. Valentina Server

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKeyDB  Xexclude from comparisonRDFox  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsHigh performance knowledge graph and semantic reasoning engineObject-relational database and reports server
Primary database modelDocument storeKey-value storeGraph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
www.oxfordsemantic.techwww.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docsdocs.keydb.devdocs.oxfordsemantic.techvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogleEQ Alpha Technology Ltd.Oxford Semantic TechnologiesParadigma Software
Initial release2008201920171999
Current release6.0, Septermber 20225.7.5
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3commercialcommercial
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 languageC++C++
Server operating systemshostedLinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesyes
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.nono
Secondary indexesyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization ProtocoRESTful HTTP API
SPARQL 1.1
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
C
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App EngineLuayes
TriggersCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
replication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLRoles, resources, and access typesfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreKeyDBRDFoxValentina Server
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