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DBMS > GeoSpock vs. Microsoft Azure Table Storage vs. Spark SQL vs. Yanza

System Properties Comparison GeoSpock vs. Microsoft Azure Table Storage vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  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 scaleA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSWide column storeRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockMicrosoftApache Software FoundationYanza
Initial release201220142015
Current release2.0, September 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesyesnono 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 systemshostedhostedLinux
OS X
Windows
Windows
Data schemeyesschema-freeyesschema-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, categoricalnonono
SQL infoSupport of SQLANSI SQL for query only (using Presto)noSQL-like DML and DDL statementsno
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
HTTP API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnononono
Triggersnononoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
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 datanooptimistic lockingnono
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 tableAccess rights based on private key authentication or shared access signaturesnono

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More resources
GeoSpockMicrosoft Azure Table StorageSpark SQLYanza
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