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DBMS > Cloudflare Workers KV vs. Databend vs. Hive vs. Trafodion vs. Vitess

System Properties Comparison Cloudflare Workers KV vs. Databend vs. Hive vs. Trafodion vs. Vitess

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonDatabend  Xexclude from comparisonHive  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.An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitydata warehouse software for querying and managing large distributed datasets, built on HadoopTransactional SQL-on-Hadoop DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational 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
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvgithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.orgtrafodion.apache.orgvitess.io
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Hometrafodion.apache.org/­documentation.htmlvitess.io/­docs
DeveloperCloudflareDatabend LabsApache Software Foundation infoinitially developed by FacebookApache Software Foundation, originally developed by HPThe Linux Foundation, PlanetScale
Initial release20182021201220142013
Current release1.0.59, April 20233.1.3, April 20222.3.0, February 201915.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC++, JavaGo
Server operating systemshostedhosted
Linux
macOS
All OS with a Java VMLinuxDocker
Linux
macOS
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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 indexesnonoyesyesyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyesyes infowith proprietary extensions
APIs and other access methodsHTTP REST
Proprietary protocol
CLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
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 proceduresnonoyes infouser defined functions and integration of map-reduceJava Stored Proceduresyes infoproprietary syntax
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneselectable replication factoryes, via HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and rolesfine 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 KVDatabendHiveTrafodionVitess
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