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DBMS > Amazon Neptune vs. Cubrid vs. GigaSpaces vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Cubrid vs. GigaSpaces vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCubrid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.82
Rank#109  Overall
#9  Graph DBMS
#5  RDF stores
Score1.44
Rank#168  Overall
#77  Relational DBMS
Score1.05
Rank#191  Overall
#31  Document stores
#6  Object oriented DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websiteaws.amazon.com/­neptunecubrid.com (korean)
cubrid.org (english)
www.gigaspaces.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcescubrid.org/­manualsdocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCUBRID Corporation, CUBRID FoundationGigaspaces TechnologiesApache Software Foundation
Initial release2017200820002014
Current release11.0, January 202115.5, September 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaJava, C++, .NetScala
Server operating systemshostedLinux
Windows
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono infoXML can be used for describing objects metadatano
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyesSQL-99 for query and DML statementsSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
OLE DB
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesno
Triggersnoyesyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Source-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole-based access controlno

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More resources
Amazon NeptuneCubridGigaSpacesSpark SQL
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