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DBMS > Amazon Neptune vs. HyperSQL vs. Postgres-XL vs. Sequoiadb vs. Spark SQL

System Properties Comparison Amazon Neptune vs. HyperSQL vs. Postgres-XL vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score3.23
Rank#93  Overall
#48  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunehsqldb.orgwww.postgres-xl.orgwww.sequoiadb.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceshsqldb.org/­web/­hsqlDocsFrame.htmlwww.postgres-xl.org/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonSequoiadb Ltd.Apache Software Foundation
Initial release201720012014 infosince 2012, originally named StormDB20132014
Current release2.7.2, June 202310 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infobased on BSD licenseOpen Source infoMozilla public licenseOpen Source infoServer: AGPL; Client: Apache V2Open 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 languageJavaCC++Scala
Server operating systemshostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
macOS
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infooid, date, timestamp, binary, regexyes
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.nonoyes infoXML type, but no XML query functionalitynono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoyesyes infodistributed, parallel query executionSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
HTTP API infoJDBC via HTTP
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC
Java
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava, SQLuser defined functionsJavaScriptno
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioningShardingyes, 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.noneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCCDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
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-standardfine grained access rights according to SQL-standardsimple password-based access controlno

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More resources
Amazon NeptuneHyperSQL infoalso known as HSQLDBPostgres-XLSequoiadbSpark SQL
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