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DBMS > GeoSpock vs. RavenDB vs. Spark SQL

System Properties Comparison GeoSpock vs. RavenDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMS
Secondary database modelsTime Series DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.47
Rank#95  Overall
#16  Document stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitegeospock.comravendb.netspark.apache.org/­sql
Technical documentationravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockHibernating RhinosApache Software Foundation
Initial release20102014
Current release2.0, September 20195.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptC#Scala
Server operating systemshostedLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nono
Secondary indexestemporal, categoricalyesno
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableno
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 tableAuthorization levels configured per client per databaseno

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More resources
GeoSpockRavenDBSpark SQL
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