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DBMS > LokiJS vs. Microsoft Access vs. Solr vs. Sphinx

System Properties Comparison LokiJS vs. Microsoft Access vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameLokiJS  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionIn-memory JavaScript DBMSMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.48
Rank#262  Overall
#42  Document stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Score6.03
Rank#60  Overall
#6  Search engines
Websitegithub.com/­techfort/­LokiJSwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.orgsphinxsearch.com
Technical documentationtechfort.github.io/­LokiJSdeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperMicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release2014199220062001
Current release1902 (16.0.11328.20222), March 20199.5.0, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Sourcecommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++JavaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Windows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typingno
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.noyes
Secondary indexesyes infovia viewsyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJavaScript APIADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesJavaScriptC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresView functions in JavaScriptyes infosince Access 2010 using the ACE-engineJava pluginsno
Triggersyesyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single collection possibleACID infobut no files for transaction loggingoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yes infobut no files for transaction loggingyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlnono infoa simple user-level security was built in till version Access 2003yesno

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