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DBMS > Amazon Aurora vs. Apache Impala vs. FatDB vs. GridGain vs. JaguarDB

System Properties Comparison Amazon Aurora vs. Apache Impala vs. FatDB vs. GridGain vs. JaguarDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonGridGain  Xexclude from comparisonJaguarDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopA .NET NoSQL DBMS that can integrate with and extend SQL Server.GridGain is an in-memory computing platform, built on Apache IgnitePerformant, highly scalable DBMS for AI and IoT applications
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Key-value store
Relational DBMS
Key-value store
Vector 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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.gridgain.comwww.jaguardb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.htmlwww.jaguardb.com/­support.html
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudGridGain Systems, Inc.DataJaguar, Inc.
Initial release20152013201220072015
Current release4.1.0, June 2022GridGain 8.5.13.3 July 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercialOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Java, C++, .NetC++ infothe server part. Clients available in other languages
Server operating systemshostedLinuxWindowsLinux
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnoyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
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
All languages supporting JDBC/ODBCC#C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceyes infovia applicationsyes (compute grid and cache interceptors can be used instead)no
Triggersyesnoyes infovia applicationsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorselectable replication factoryes (replicated cache)Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
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 Kerberosno infoCan implement custom security layer via applicationsSecurity Hooks for custom implementationsrights management via user accounts

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More resources
Amazon AuroraApache ImpalaFatDBGridGainJaguarDB
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