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DBMS > Cloudflare Workers KV vs. Databend vs. Google Cloud Bigtable vs. Hive vs. Trafodion

System Properties Comparison Cloudflare Workers KV vs. Databend vs. Google Cloud Bigtable vs. Hive vs. Trafodion

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonDatabend  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonTrafodion  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 complexityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on HadoopTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Relational DBMSRelational 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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvgithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­bigtablehive.apache.orgtrafodion.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.databend.comcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Hometrafodion.apache.org/­documentation.html
DeveloperCloudflareDatabend LabsGoogleApache Software Foundation infoinitially developed by FacebookApache Software Foundation, originally developed by HP
Initial release20182021201520122014
Current release1.0.59, April 20233.1.3, April 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC++, Java
Server operating systemshostedhosted
Linux
macOS
hostedAll OS with a Java VMLinux
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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.nononono
Secondary indexesnononoyesyes
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsHTTP REST
Proprietary protocol
CLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnononoyes infouser defined functions and integration of map-reduceJava Stored Procedures
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factoryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoquery execution via MapReduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesAtomic single-row operationsnoACID
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.nonono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Cloudflare Workers KVDatabendGoogle Cloud BigtableHiveTrafodion
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