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DBMS > Amazon Aurora vs. EXASOL vs. Hazelcast vs. Hive vs. Kdb

System Properties Comparison Amazon Aurora vs. EXASOL vs. Hazelcast vs. Hive vs. Kdb

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance Time Series DBMS
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMSTime Series DBMS
Vector DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score7.70
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comhazelcast.comhive.apache.orgkx.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourceshazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homecode.kx.com
DeveloperAmazonExasolHazelcastApache Software Foundation infoinitially developed by FacebookKx Systems, a division of First Derivatives plc
Initial release20152000200820122000 infokdb was released 2000, kdb+ in 2003
Current release5.3.6, November 20233.1.3, April 20223.6, May 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2commercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaq
Server operating systemshostedAll OS with a Java VMAll OS with a Java VMLinux
OS X
Solaris
Windows
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.yesnoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLyesyesSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (q)
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reduceuser defined functions
Triggersyesyesyes infoEventsnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyesyes infoquery execution via MapReduceno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednono
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.yesyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardRole-based access controlAccess rights for users, groups and rolesrights management via user accounts
More information provided by the system vendor
Amazon AuroraEXASOLHazelcastHiveKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Amazon AuroraEXASOLHazelcastHiveKdb
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