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DBMS > Hyprcubd vs. Spark SQL vs. Yanza

System Properties Comparison Hyprcubd vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionServerless Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitehyprcubd.com (offline)spark.apache.org/­sqlyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHyprcubd, Inc.Apache Software FoundationYanza
Initial release20142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScala
Server operating systemshostedLinux
OS X
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesno
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
Secondary indexesnonono
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (https)JDBC
ODBC
HTTP API
Supported programming languagesJava
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonono
Triggersnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datanoyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controltoken accessnono

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More resources
HyprcubdSpark SQLYanza
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