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DBMS > Databricks vs. Hive vs. Linter vs. RavenDB

System Properties Comparison Databricks vs. Hive vs. Linter vs. RavenDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHive  Xexclude from comparisonLinter  Xexclude from comparisonRavenDB  Xexclude from comparison
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.data warehouse software for querying and managing large distributed datasets, built on HadoopRDBMS for high security requirementsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSDocument store
Secondary database modelsSpatial DBMSGraph DBMS
Spatial DBMS
Time 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitewww.databricks.comhive.apache.orglinter.ruravendb.net
Technical documentationdocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Homeravendb.net/­docs
DeveloperDatabricksApache Software Foundation infoinitially developed by Facebookrelex.ruHibernating Rhinos
Initial release2013201219902010
Current release3.1.3, April 20225.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C#
Server operating systemshostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesPython
R
Scala
C++
Java
PHP
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reduceyes infoproprietary syntax with the possibility to convert from PL/SQLyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate 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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, Cluster-wide transaction available
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.no
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAuthorization levels configured per client per database
More information provided by the system vendor
DatabricksHiveLinterRavenDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHiveLinterRavenDB
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