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DBMS > Apache Druid vs. Databricks vs. Solr vs. Valentina Server

System Properties Comparison Apache Druid vs. Databricks vs. Solr vs. Valentina Server

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataThe 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.A widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitedruid.apache.orgwww.databricks.comsolr.apache.orgwww.valentina-db.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comsolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation and contributorsDatabricksApache Software FoundationParadigma Software
Initial release2012201320061999
Current release29.0.1, April 20249.5.0, February 20245.7.5
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyes
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.noyesyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingwith Databricks SQLSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnouser defined functions and aggregatesJava pluginsyes
Triggersnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidDatabricksSolrValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidDatabricksSolrValentina Server
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