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DBMS > Linter vs. Quasardb vs. Solr vs. Splice Machine

System Properties Comparison Linter vs. Quasardb vs. Solr vs. Splice Machine

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Editorial information provided by DB-Engines
NameLinter  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionRDBMS for high security requirementsDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache LuceneOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitelinter.ruquasar.aisolr.apache.orgsplicemachine.com
Technical documentationdoc.quasar.ai/­mastersolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
Developerrelex.ruquasardbApache Software FoundationSplice Machine
Initial release1990200920062014
Current release3.14.1, January 20249.6.0, April 20243.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++JavaJava
Server operating systemsAIX
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)Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyes 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.nonoyes
Secondary indexesyesyes infowith tagsyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like query languageSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP APIJava API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoproprietary syntax with the possibility to convert from PL/SQLnoJava pluginsyes infoJava
Triggersyesnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoconsistent hashingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTransient modeyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailyesAccess rights for users, groups and roles according to SQL-standard

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LinterQuasardbSolrSplice Machine
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