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DBMS > Amazon Aurora vs. Apache Impala vs. Fujitsu Enterprise Postgres

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Fujitsu Enterprise Postgres

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument storeDocument store
Spatial DBMS
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
Score0.31
Rank#285  Overall
#129  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.postgresql.fastware.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manuals
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software Technology
Initial release20152013
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemshostedLinuxLinux
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functions
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingpartitioning by range, list and by hash
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorSource-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 integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon AuroraApache ImpalaFujitsu Enterprise Postgres
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Amazon AuroraApache ImpalaFujitsu Enterprise Postgres
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Recent citations in the news

Baffle enables computation on encrypted Amazon RDS and Aurora data – Blocks and Files
1 May 2024, Blocks and Files

Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora
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28 November 2017, SDTimes.com

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Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

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