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DBMS > Amazon Aurora vs. GridGain vs. HEAVY.AI vs. IBM Cloudant vs. Kinetica

System Properties Comparison Amazon Aurora vs. GridGain vs. HEAVY.AI vs. IBM Cloudant vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDatabase as a Service offering based on Apache CouchDBFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.68
Rank#106  Overall
#20  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­cloudantwww.kinetica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.gridgain.com/­docs/­index.htmldocs.heavy.aicloud.ibm.com/­docs/­Cloudantdocs.kinetica.com
DeveloperAmazonGridGain Systems, Inc.HEAVY.AI, Inc.IBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Kinetica
Initial release20152007201620102012
Current releaseGridGain 8.5.15.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++ and CUDAErlangC, C++
Server operating systemshostedLinux
OS X
Solaris
Windows
LinuxhostedLinux
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.yesyesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
RESTful HTTP/JSON APIJDBC
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
C#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)noView functions (Map-Reduce) in JavaScriptuser defined functions
Triggersyesyes (cache interceptors and events)noyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Multi-source replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic lockingyes
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.yesyesyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAccess rights for users and roles on table level

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More resources
Amazon AuroraGridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM CloudantKinetica
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