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

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

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionServerless Time Series DBMSDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark 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 method
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitehyprcubd.com (offline)github.com/­reductstore
www.reduct.store
spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHyprcubd, Inc.ReductStore LLCApache Software FoundationSTS Soft SC
Initial release202320142011
Current release1.9, March 20243.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, RustScalaC#
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesyes infoprimitive types and user defined types (classes)
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
Secondary indexesnonono
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (https)HTTP APIJDBC
ODBC
.NET Client API
Supported programming languagesC++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnonono
Triggersnonono
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 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
HyprcubdReductStoreSpark SQLSTSdb
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