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DBMS > Cloudflare Workers KV vs. DataFS vs. Google Cloud Datastore vs. GridGain

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

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparison
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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelKey-value storeObject oriented DBMSDocument storeKey-value store
Relational DBMS
Secondary database modelsGraph 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvnewdatabase.comcloud.google.com/­datastorewww.gridgain.com
Technical documentationdevelopers.cloudflare.com/­kv/­apidev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.html
DeveloperCloudflareMobiland AGGoogleGridGain Systems, Inc.
Initial release2018201820082007
Current release1.1.263, October 2022GridGain 8.5.1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemshostedWindowshostedLinux
OS X
Solaris
Windows
Data schemeschema-freeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyes
Typing infopredefined data types such as float or datenoyesyes, 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.nononoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsHTTP REST
Proprietary protocol
.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)
Triggersnono, except callback-events from server when changes happenedCallbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
Cloudflare Workers KVDataFSGoogle Cloud DatastoreGridGain
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