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DBMS > Amazon Aurora vs. Hazelcast vs. jBASE vs. Spark SQL vs. Stardog

System Properties Comparison Amazon Aurora vs. Hazelcast vs. jBASE vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHazelcast  Xexclude from comparisonjBASE  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA widely adopted in-memory data gridA robust multi-value DBMS comprising development tools and middlewareSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSKey-value storeMultivalue DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­rds/­aurorahazelcast.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasespark.apache.org/­sqlwww.stardog.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlhazelcast.org/­imdg/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9spark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperAmazonHazelcastRocket Software (formerly Zumasys)Apache Software FoundationStardog-Union
Initial release20152008199120142010
Current release5.3.6, November 20235.73.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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 languageJavaScalaJava
Server operating systemshostedAll OS with a Java VMAIX
Linux
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-freeschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesoptionalyesyes
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 strategyyesnono infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesSQL-like query languageEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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
Basic
Jabbascript
Java
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyesnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesyes infoEventsyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapyesnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDnoACID
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.yesyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess rights can be defined down to the item levelnoAccess rights for users and roles

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More resources
Amazon AuroraHazelcastjBASESpark SQLStardog
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