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DBMS > Amazon Aurora vs. GigaSpaces vs. Hazelcast vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Amazon Aurora vs. GigaSpaces vs. Hazelcast vs. Percona Server for MongoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHazelcast  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely adopted in-memory data gridA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Key-value storeDocument storeRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Document 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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.52
Rank#254  Overall
#39  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.gigaspaces.comhazelcast.comwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.gigaspaces.com/­latest/­landing.htmlhazelcast.org/­imdg/­docsdocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGigaspaces TechnologiesHazelcastPerconaApache Software Foundation
Initial release20152000200820152014
Current release15.5, September 20205.3.6, November 20233.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC++Scala
Server operating systemshostedLinux
macOS
Solaris
Windows
All OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
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.yesno infoXML can be used for describing objects metadatayes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-99 for query and DML statementsSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
proprietary protocol using JSONJDBC
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++
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesyes infoEvent Listeners, Executor ServicesJavaScriptno
Triggersyesyes, event driven architectureyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoReplicated MapSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
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 infovia In-Memory Engineno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlRole-based access controlAccess rights for users and rolesno

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More resources
Amazon AuroraGigaSpacesHazelcastPercona Server for MongoDBSpark SQL
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