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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  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 networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Document store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.databricks.com
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsDatabricksDrizzle project, originally started by Brian Aker
Initial release20152013201620132008
Current release4.1.0, June 202217037.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercialOpen Source infoGNU GPL
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemshostedLinuxLinuxhostedFreeBSD
Linux
OS X
Data schemeyesyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesoptionalyes
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.yesnoyesyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnowith Databricks SQLyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
LDAPJDBC
ODBC
RESTful HTTP API
JDBC
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 bindingsPython
R
Scala
C
C++
Java
PHP
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenouser defined functions and aggregatesno
Triggersyesnoyesno infohooks for callbacks inside the server can be used.
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infocell divisionSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic execution of specific operationsACIDACID
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.yesnoyesno
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, HTTP
More information provided by the system vendor
Amazon AuroraApache ImpalaAtos Standard Common RepositoryDatabricksDrizzle
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon AuroraApache ImpalaAtos Standard Common RepositoryDatabricksDrizzle
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