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DBMS > LMDB vs. NCache vs. Solr vs. Sphinx

System Properties Comparison LMDB vs. NCache vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameLMDB  Xexclude from comparisonNCache  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA high performant, light-weight, embedded key-value database libraryOpen-Source and Enterprise in-memory Key-Value StoreA 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 modelKey-value storeKey-value storeSearch engineSearch engine
Secondary database modelsDocument store
Search engine infoUsing distributed Lucene
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#121  Overall
#20  Key-value stores
Score0.96
Rank#195  Overall
#29  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.symas.com/­symas-embedded-database-lmdbwww.alachisoft.com/­ncachesolr.apache.orgsphinxsearch.com
Technical documentationwww.lmdb.tech/­docwww.alachisoft.com/­resources/­docssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperSymasAlachisoftApache Software FoundationSphinx Technologies Inc.
Initial release2011200520062001
Current release0.9.32, January 20245.3.3, April 20249.6.1, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoEnterprise Edition availableOpen 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 languageCC#, .NET, .NET Core, JavaJavaC++
Server operating systemsLinux
Unix
Windows
Linux
Windows
All 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-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datepartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes 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.nonoyes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Solr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsIDistributedCache
JCache
LINQ
Proprietary native API
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
.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 proceduresnono infosupport for stored procedures with SQL-Server CLRJava pluginsno
Triggersnoyes infoNotificationsyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneyesShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, with selectable consistency levelyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic locking and pessimistic lockingoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesyes
User concepts infoAccess controlnoAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)yesno
More information provided by the system vendor
LMDBNCacheSolrSphinx
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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LMDBNCacheSolrSphinx
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