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DBMS > Apache Druid vs. BaseX vs. Databricks vs. Linter

System Properties Comparison Apache Druid vs. BaseX vs. Databricks vs. Linter

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBaseX  Xexclude from comparisonDatabricks  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.The 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.RDBMS for high security requirements
Primary database modelRelational DBMS
Time Series DBMS
Native XML DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score1.56
Rank#141  Overall
#4  Native XML DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.03
Rank#368  Overall
#156  Relational DBMS
Websitedruid.apache.orgbasex.orgwww.databricks.comlinter.ru
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.basex.orgdocs.databricks.com
DeveloperApache Software Foundation and contributorsBaseX GmbHDatabricksrelex.ru
Initial release2012200720131990
Current release30.0.0, June 202411.2, August 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSD licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyes infoschema-less columns are supportedschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyes
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.noyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnowith Databricks SQLyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
Python
R
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresnoyesuser defined functions and aggregatesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnoyes infovia eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writerACIDACID
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization concept on 4 levelsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidBaseXDatabricksLinter
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidBaseXDatabricksLinter
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