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DBMS > Amazon Aurora vs. Apache Impala vs. Databricks vs. Oracle Berkeley DB

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Databricks vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopThe 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.Widely used in-process key-value store
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.databricks.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015201320131994
Current release4.1.0, June 202218.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesno
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 infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementswith Databricks SQLyes infoSQL interfaced based on SQLite is available
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
RESTful HTTP 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
All languages supporting JDBC/ODBCPython
R
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersyesnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesSource-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
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno
More information provided by the system vendor
Amazon AuroraApache ImpalaDatabricksOracle Berkeley DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraApache ImpalaDatabricksOracle Berkeley DB
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