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DBMS > Amazon Aurora vs. Apache Impala vs. Atos Standard Common Repository vs. Drizzle vs. HEAVY.AI

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Atos Standard Common Repository vs. Drizzle vs. HEAVY.AI

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDrizzle  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.heavy.ai
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.
Initial release20152013201620082016
Current release4.1.0, June 202217037.2.4, September 20125.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition available
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 languageC++JavaC++C++ and CUDA
Server operating systemshostedLinuxLinuxFreeBSD
Linux
OS X
Linux
Data schemeyesyesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesyesoptionalyesyes
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.yesnoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes infowith proprietary extensionsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
LDAPJDBCJDBC
ODBC
Thrift
Vega
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C++
Java
PHP
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenonono
Triggersyesnoyesno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infocell divisionShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesMulti-source replication
Source-replica replication
Multi-source replication
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 Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic execution of specific operationsACIDno
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.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache ImpalaAtos Standard Common RepositoryDrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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