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DBMS > Databend vs. Hawkular Metrics vs. HBase vs. Hive

System Properties Comparison Databend vs. Hawkular Metrics vs. HBase vs. Hive

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.hawkular.orghbase.apache.orghive.apache.org
Technical documentationdocs.databend.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDatabend LabsCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release2021201420082012
Current release1.0.59, April 20232.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaJavaJava
Server operating systemshosted
Linux
macOS
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 indexesnononoyes
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HTTP RESTJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
Triggersnoyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoSingle row ACID (across millions of columns)no
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.noyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles

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More resources
DatabendHawkular MetricsHBaseHive
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