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DBMS > GeoMesa vs. Quasardb vs. SiteWhere vs. Spark SQL

System Properties Comparison GeoMesa vs. Quasardb vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonQuasardb  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Distributed, high-performance timeseries databaseM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSpatial DBMSTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.geomesa.orgquasar.aigithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldoc.quasar.ai/­mastersitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCCRi and othersquasardbSiteWhereApache Software Foundation
Initial release2014200920102014
Current release4.0.5, February 20243.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++JavaScala
Server operating systemsBSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freepredefined schemeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesyes
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 indexesyesyes infowith tagsnono
SQL infoSupport of SQLnoSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsHTTP APIHTTP RESTJDBC
ODBC
Supported programming languages.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoconsistent hashingSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerSource-replica replication with selectable replication factorselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layeryes infoTransient modenono
User concepts infoAccess controlyes infodepending on the DBMS used for storageCryptographically strong user authentication and audit trailUsers with fine-grained authorization conceptno

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More resources
GeoMesaQuasardbSiteWhereSpark SQL
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