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DBMS > GeoSpock vs. Spark SQL vs. TDSQL for MySQL vs. Yanza

System Properties Comparison GeoSpock vs. Spark SQL vs. TDSQL for MySQL vs. Yanza

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonYanza  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processingA 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.Time Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitegeospock.comspark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdbyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperGeoSpockApache Software FoundationTencentYanza
Initial release201420132015
Current release2.0, September 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptScala
Server operating systemshostedLinux
OS X
Windows
hostedWindows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nononono
Secondary indexestemporal, categoricalnoyesno
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like DML and DDL statementsyesno
APIs and other access methodsJDBCJDBC
ODBC
JDBC
ODBC
HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingyes, utilizing Spark CoreAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 controlAccess rights for users can be defined per tablenoUsers with fine-grained authorization conceptno

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More resources
GeoSpockSpark SQLTDSQL for MySQLYanza
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