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DBMS > Databricks vs. Linter vs. Quasardb vs. Solr

System Properties Comparison Databricks vs. Linter vs. Quasardb vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLinter  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  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.RDBMS for high security requirementsDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comlinter.ruquasar.aisolr.apache.org
Technical documentationdocs.databricks.comdoc.quasar.ai/­mastersolr.apache.org/­resources.html
DeveloperDatabricksrelex.ruquasardbApache Software Foundation
Initial release2013199020092006
Current release3.14.1, January 20249.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++Java
Server operating systemshostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
BSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyes infosupports customizable data types and automatic typing
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.yesnonoyes
Secondary indexesyesyesyes infowith tagsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoproprietary syntax with the possibility to convert from PL/SQLnoJava plugins
Triggersyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailyes
More information provided by the system vendor
DatabricksLinterQuasardbSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLinterQuasardbSolr
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