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DBMS > Cloudflare Workers KV vs. DataFS vs. GeoSpock vs. Google Cloud Datastore vs. Trafodion

System Properties Comparison Cloudflare Workers KV vs. DataFS vs. GeoSpock vs. Google Cloud Datastore vs. Trafodion

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonDataFS  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTrafodion  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Spatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value storeObject oriented DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsGraph DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitewww.cloudflare.com/­developer-platform/­workers-kvnewdatabase.comgeospock.comcloud.google.com/­datastoretrafodion.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apidev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docstrafodion.apache.org/­documentation.html
DeveloperCloudflareMobiland AGGeoSpockGoogleApache Software Foundation, originally developed by HP
Initial release2018201820082014
Current release1.1.263, October 20222.0, September 20192.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++, Java
Server operating systemshostedWindowshostedhostedLinux
Data schemeschema-freeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes, details hereyes
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.nonononono
Secondary indexesnonotemporal, categoricalyesyes
SQL infoSupport of SQLnonoANSI SQL for query only (using Presto)SQL-like query language (GQL)yes
APIs and other access methodsHTTP REST
Proprietary protocol
.NET Client API
Proprietary client DLL
WinRT client
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonousing Google App EngineJava Stored Procedures
Triggersnono, except callback-events from server when changes happenednoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integritynoyesnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononono
User concepts infoAccess controlWindows-ProfileAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Cloudflare Workers KVDataFSGeoSpockGoogle Cloud DatastoreTrafodion
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