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DBMS > Cloudflare Workers KV vs. Databend vs. Hive vs. IBM Db2 Event Store vs. Trafodion

System Properties Comparison Cloudflare Workers KV vs. Databend vs. Hive vs. IBM Db2 Event Store vs. Trafodion

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonDatabend  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  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 complexitydata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value storeRelational DBMSRelational DBMSEvent Store
Time Series DBMS
Relational 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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvgithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.orgwww.ibm.com/­products/­db2-event-storetrafodion.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storetrafodion.apache.org/­documentation.html
DeveloperCloudflareDatabend LabsApache Software Foundation infoinitially developed by FacebookIBMApache Software Foundation, originally developed by HP
Initial release20182021201220172014
Current release1.0.59, April 20233.1.3, April 20222.02.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache 2.0
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 and C++C++, Java
Server operating systemshostedhosted
Linux
macOS
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
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.nononono
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeyes
APIs and other access methodsHTTP REST
Proprietary protocol
CLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceyesJava Stored Procedures
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneselectable replication factorActive-active shard replicationyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Cloudflare Workers KVDatabendHiveIBM Db2 Event StoreTrafodion
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