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DBMS > Databricks vs. GeoSpock vs. Heroic

System Properties Comparison Databricks vs. GeoSpock vs. Heroic

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeoSpock  Xexclude from comparisonHeroic  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Spatial and temporal data processing engine for extreme data scaleTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websitewww.databricks.comgeospock.comgithub.com/­spotify/­heroic
Technical documentationdocs.databricks.comspotify.github.io/­heroic
DeveloperDatabricksGeoSpockSpotify
Initial release20132014
Current release2.0, September 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJava
Server operating systemshostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyestemporal, categoricalyes infovia Elasticsearch
SQL infoSupport of SQLwith Databricks SQLANSI SQL for query only (using Presto)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesPython
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.nonono
User concepts infoAccess controlAccess rights for users can be defined per table
More information provided by the system vendor
DatabricksGeoSpockHeroic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGeoSpockHeroic
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