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DBMS > Hyprcubd vs. Spark SQL vs. STSdb vs. TDSQL for MySQL

System Properties Comparison Hyprcubd vs. Spark SQL vs. STSdb vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTDSQL for MySQL  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 high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitehyprcubd.com (offline)spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.tencentcloud.com/­products/­dcdb
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperHyprcubd, Inc.Apache Software FoundationSTS Soft SCTencent
Initial release201420112013
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 availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC#
Server operating systemshostedLinux
OS X
Windows
Windowshosted
Data schemeyesyesyesyes
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 statementsnoyes
APIs and other access methodsgRPC (https)JDBC
ODBC
.NET Client APIJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C#
Java
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica 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 accessnonoUsers with fine-grained authorization concept

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More resources
HyprcubdSpark SQLSTSdbTDSQL for MySQL
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