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DBMS > Hyprcubd vs. Spark SQL vs. STSdb vs. Tkrzw

System Properties Comparison Hyprcubd vs. Spark SQL vs. STSdb vs. Tkrzw

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Hyprcubd 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 processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSRelational DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitehyprcubd.com (offline)spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4dbmx.net/­tkrzw
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHyprcubd, Inc.Apache Software FoundationSTS Soft SCMikio Hirabayashi
Initial release201420112020
Current release3.5.0 ( 2.13), September 20234.0.8, September 20150.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC#C++
Server operating systemshostedLinux
OS X
Windows
WindowsLinux
macOS
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesyes infoprimitive types and user defined types (classes)no
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 statementsnono
APIs and other access methodsgRPC (https)JDBC
ODBC
.NET Client API
Supported programming languagesJava
Python
R
Scala
C#
Java
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datanoyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controltoken accessnonono

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More resources
HyprcubdSpark SQLSTSdbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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