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DBMS > Amazon Aurora vs. Drizzle vs. GridDB vs. Impala

System Properties Comparison Amazon Aurora vs. Drizzle vs. GridDB vs. Impala

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonImpala  Xexclude from comparison
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 AmazonMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big DataAnalytic DBMS for Hadoop
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.58
Rank#44  Overall
#28  Relational DBMS
Score1.37
Rank#144  Overall
#10  Time Series DBMS
Score18.75
Rank#37  Overall
#23  Relational DBMS
Websiteaws.amazon.com/­rds/­auroragriddb.netwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.griddb.netdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperAmazonDrizzle project, originally started by Brian AkerToshiba CorporationCloudera
Initial release2015200820132013
Current release7.2.4, September 20124.6, February 20213.4.0, April 2020
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2
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 systemshostedFreeBSD
Linux
OS X
LinuxLinux
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCProprietary protocolJDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresyesnonoyes infouser defined functions and integration of map-reduce
Triggersyesno infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelno
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos
More information provided by the system vendor
Amazon AuroraDrizzleGridDBImpala
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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More resources
Amazon AuroraDrizzleGridDBImpala
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