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DBMS > Amazon Aurora vs. Hive vs. LeanXcale vs. Prometheus

System Properties Comparison Amazon Aurora vs. Hive vs. LeanXcale vs. Prometheus

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHive  Xexclude from comparisonLeanXcale  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by Amazondata warehouse software for querying and managing large distributed datasets, built on HadoopA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteaws.amazon.com/­rds/­aurorahive.apache.orgwww.leanxcale.comprometheus.io
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homeprometheus.io/­docs
DeveloperAmazonApache Software Foundation infoinitially developed by FacebookLeanXcale
Initial release2015201220152015
Current release3.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemshostedAll OS with a Java VMLinux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data only
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.yesno infoImport of XML data possible
Secondary indexesyesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infothrough Apache Derbyno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP/JSON API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Java
PHP
Python
C
Java
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesno

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More resources
Amazon AuroraHiveLeanXcalePrometheus
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