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DBMS > Cloudflare Workers KV vs. Google Cloud Datastore vs. Trafodion vs. Vitess

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

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTrafodion  Xexclude from comparisonVitess  Xexclude from comparison
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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTransactional SQL-on-Hadoop DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#274  Overall
#39  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvcloud.google.com/­datastoretrafodion.apache.orgvitess.io
Technical documentationdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docstrafodion.apache.org/­documentation.htmlvitess.io/­docs
DeveloperCloudflareGoogleApache Software Foundation, originally developed by HPThe Linux Foundation, PlanetScale
Initial release2018200820142013
Current release2.3.0, February 201915.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaGo
Server operating systemshostedhostedLinuxDocker
Linux
macOS
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyes infowith proprietary extensions
APIs and other access methodsHTTP REST
Proprietary protocol
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnousing Google App EngineJava Stored Proceduresyes infoproprietary syntax
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes, via HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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 controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Cloudflare Workers KVGoogle Cloud DatastoreTrafodionVitess
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