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DBMS > GeoSpock vs. HBase vs. Spark SQL vs. Yanza

System Properties Comparison GeoSpock vs. HBase vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHBase  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 scaleWide-column store based on Apache Hadoop and on concepts of BigTableSpark 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comhbase.apache.orgspark.apache.org/­sqlyanza.com
Technical documentationhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationYanza
Initial release200820142015
Current release2.0, September 20192.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaScala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Windows
Data schemeyesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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 methodsJDBCJava API
RESTful HTTP API
Thrift
JDBC
ODBC
HTTP API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanono
Triggersnoyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)nono
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.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono

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More resources
GeoSpockHBaseSpark SQLYanza
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