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DBMS > Amazon Aurora vs. Hazelcast vs. Microsoft Azure Table Storage vs. Netezza vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Hazelcast vs. Microsoft Azure Table Storage vs. Netezza vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorahazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezzaspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonHazelcastMicrosoftIBMApache Software Foundation
Initial release20152008201220002014
Current release5.3.6, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedAll OS with a Java VMhostedLinux infoincluded in applianceLinux
OS X
Windows
Data schemeyesschema-freeschema-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.yesyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesSQL-like query languagenoyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
OLE DB
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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesnoyesno
Triggersyesyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACIDno
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.yesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptno

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More resources
Amazon AuroraHazelcastMicrosoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMSpark SQL
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