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DBMS > Databend vs. Hive vs. Postgres-XL vs. Quasardb

System Properties Comparison Databend vs. Hive vs. Postgres-XL vs. Quasardb

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHive  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  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 complexitydata warehouse software for querying and managing large distributed datasets, built on HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries database
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.orgwww.postgres-xl.orgquasar.ai
Technical documentationdocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.postgres-xl.org/­documentationdoc.quasar.ai/­master
DeveloperDatabend LabsApache Software Foundation infoinitially developed by Facebookquasardb
Initial release202120122014 infosince 2012, originally named StormDB2009
Current release1.0.59, April 20233.1.3, April 202210 R1, October 20183.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageRustJavaCC++
Server operating systemshosted
Linux
macOS
All OS with a Java VMLinux
macOS
BSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyesyes infowith tags
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infodistributed, parallel query executionSQL-like query language
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and rolesfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail

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More resources
DatabendHivePostgres-XLQuasardb
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