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

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

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonYDB  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 distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelTime Series DBMSRelational DBMSKey-value storeDocument store
Relational DBMS
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
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitehyprcubd.com (offline)spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4github.com/­ydb-platform/­ydb
ydb.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperHyprcubd, Inc.Apache Software FoundationSTS Soft SCYandex
Initial release201420112019
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoApache 2.0; 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 languageGoScalaC#
Server operating systemshostedLinux
OS X
Windows
WindowsLinux
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesyes infoprimitive types and user defined types (classes)yes
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 indexesnononoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoSQL-like query language (YQL)
APIs and other access methodsgRPC (https)JDBC
ODBC
.NET Client APIRESTful HTTP API (DynamoDB compatible)
Supported programming languagesJava
Python
R
Scala
C#
Java
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnononono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneActive-passive shard replication
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 datanononoACID
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.nonono
User concepts infoAccess controltoken accessnonoAccess rights defined for Yandex Cloud users

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More resources
HyprcubdSpark SQLSTSdbYDB
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