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DBMS > HyperSQL vs. Postgres-XL vs. Riak TS vs. Sequoiadb vs. Spark SQL

System Properties Comparison HyperSQL vs. Postgres-XL vs. Riak TS vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameHyperSQL infoalso known as HSQLDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonRiak TS  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series 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
Score3.23
Rank#93  Overall
#48  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitehsqldb.orgwww.postgres-xl.orgwww.sequoiadb.comspark.apache.org/­sql
Technical documentationhsqldb.org/­web/­hsqlDocsFrame.htmlwww.postgres-xl.org/­documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latestwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOpen Source, formerly Basho TechnologiesSequoiadb Ltd.Apache Software Foundation
Initial release20012014 infosince 2012, originally named StormDB201520132014
Current release2.7.2, June 202310 R1, October 20183.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infobased on BSD licenseOpen Source infoMozilla public licenseOpen SourceOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCErlangC++Scala
Server operating systemsAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
macOS
Linux
OS X
LinuxLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes 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.noyes infoXML type, but no XML query functionalitynonono
Secondary indexesyesyesrestrictedyesno
SQL infoSupport of SQLyesyes infodistributed, parallel query executionyes, limitedSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsHTTP API infoJDBC via HTTP
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Native Erlang Interface
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC
Java
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava, SQLuser defined functionsErlangJavaScriptno
Triggersyesyesyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesno infolinks between datasets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoMVCCnoDocument is locked during a transactionno
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnosimple password-based access controlno

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More resources
HyperSQL infoalso known as HSQLDBPostgres-XLRiak TSSequoiadbSpark SQL
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