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DBMS > LokiJS vs. Microsoft Access vs. Percona Server for MongoDB vs. Solr vs. Spark SQL

System Properties Comparison LokiJS vs. Microsoft Access vs. Percona Server for MongoDB vs. Solr vs. Spark SQL

Editorial information provided by DB-Engines
NameLokiJS  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  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 drop-in replacement for MongoDB Community Edition with enterprise-grade features.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.43
Rank#264  Overall
#42  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­techfort/­LokiJSwww.microsoft.com/­en-us/­microsoft-365/­accesswww.percona.com/­mongodb/­software/­percona-server-for-mongodbsolr.apache.orgspark.apache.org/­sql
Technical documentationtechfort.github.io/­LokiJSdeveloper.microsoft.com/­en-us/­accessdocs.percona.com/­percona-distribution-for-mongodbsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftPerconaApache Software FoundationApache Software Foundation
Initial release20141992201520062014
Current release1902 (16.0.11328.20222), March 20193.4.10-2.10, November 20179.5.0, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Sourcecommercial infoBundled with Microsoft OfficeOpen Source infoGPL Version 2Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++C++JavaScala
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Windows infoNot a real database server, but making use of DLLsLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyesyes 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.nonoyesno
Secondary indexesyes infovia viewsyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJavaScript APIADO.NET
DAO
ODBC
OLE DB
proprietary protocol using JSONJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesJavaScriptC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresView functions in JavaScriptyes infosince Access 2010 using the ACE-engineJavaScriptJava pluginsno
Triggersyesyes infosince Access 2010 using the ACE-enginenoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
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 loggingnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 loggingyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infovia In-Memory Engineyesno
User concepts infoAccess controlnono infoa simple user-level security was built in till version Access 2003Access rights for users and rolesyesno

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More resources
LokiJSMicrosoft AccessPercona Server for MongoDBSolrSpark SQL
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