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

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

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  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 DBMSOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingA 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 DBMSTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitehyprcubd.com (offline)prometheus.iospark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHyprcubd, Inc.Apache Software FoundationMikio Hirabayashi
Initial release201520142020
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open 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 languageGoGoScalaC++
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringNumeric data onlyyesno
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.nono infoImport of XML data possiblenono
Secondary indexesnonono
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (https)RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby Federationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate 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.nononoyes infousing specific database classes
User concepts infoAccess controltoken accessnonono

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More resources
HyprcubdPrometheusSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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