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

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

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Editorial information provided by DB-Engines
NameFirebolt  Xexclude from comparisonGeoSpock  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.
DescriptionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseSpatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.firebolt.iogeospock.comspark.apache.org/­sqlyanza.com
Technical documentationdocs.firebolt.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFirebolt Analytics Inc.GeoSpockApache Software FoundationYanza
Initial release202020142015
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 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.nonono
Secondary indexesyestemporal, categoricalnono
SQL infoSupport of SQLyesANSI SQL for query only (using Presto)SQL-like DML and DDL statementsno
APIs and other access methods.Net
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
HTTP API
Supported programming languagesGo
JavaScript (Node.js)
Python
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 shardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users can be defined per tablenono

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More resources
FireboltGeoSpockSpark SQLYanza
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