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DBMS > Amazon Aurora vs. Apache Impala vs. GridDB vs. MaxDB

System Properties Comparison Amazon Aurora vs. Apache Impala vs. GridDB vs. MaxDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataA robust and reliable RDBMS optimized to run all major SAP solutions
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument storeKey-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.32
Rank#112  Overall
#55  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orggriddb.netmaxdb.sap.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.griddb.netmaxdb.sap.com/­documentation
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationSAP, acquired from Software AG (Adabas-D) in 1997
Initial release2015201320131984
Current release4.1.0, June 20225.1, August 20227.9.10.12, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infoLimited community edition free
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 languageC++C++C++
Server operating systemshostedLinuxLinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
WebDAV
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/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenoyes
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelACID
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.yesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon AuroraApache ImpalaGridDBMaxDB infoformerly named Adabas-D
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon AuroraApache ImpalaGridDBMaxDB infoformerly named Adabas-D
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