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DBMS > Amazon Aurora vs. EXASOL vs. GridDB vs. Hazelcast

System Properties Comparison Amazon Aurora vs. EXASOL vs. GridDB vs. Hazelcast

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Scalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value store
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.64
Rank#45  Overall
#28  Relational DBMS
Score3.09
Rank#92  Overall
#45  Relational DBMS
Score0.61
Rank#205  Overall
#11  Time Series DBMS
Score8.45
Rank#48  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­aurorawww.exasol.com/­en/­productsgriddb.nethazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­en/­community/­resourcesdocs.griddb.nethazelcast.org/­imdg/­docs
DeveloperAmazonExasolToshiba CorporationHazelcast
Initial release2015200020132008
Current release4.5, June 20204.0, February 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses available
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++Java
Server operating systemshostedLinuxAll OS with a Java VM
Data schemeyesyesyesschema-free
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.yesnonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyesSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
Proprietary protocolJCache
JPA
Memcached protocol
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
Java
Lua
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnoyes infoEvent Listeners, Executor Services
Triggersyesyesyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-slave replicationyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelone or two-phase-commit; repeatable reads; read commited
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.yesyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users can be defined per databaseRole-based access control
More information provided by the system vendor
Amazon AuroraEXASOLGridDBHazelcast
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Hazelcast is an in-memory computing platform that runs applications with extremely...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Hazelcast has an optimized, multi-threaded architecture that enables the highest...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Hazelcast powers many types of large-scale, data processing applications. A sample...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Hazelcast customers include 50 of the world’s largest financial services companies,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Hazelcast provides both open source and commercial software. The open source offering...
» more

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More resources
Amazon AuroraEXASOLGridDBHazelcast
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