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DBMS > Hazelcast vs. Lovefield vs. mSQL vs. Solr vs. Sphinx

System Properties Comparison Hazelcast vs. Lovefield vs. mSQL vs. Solr vs. Sphinx

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonLovefield  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA widely adopted in-memory data gridEmbeddable relational database for web apps written in pure JavaScriptmSQL (Mini SQL) is a simple and lightweight RDBMSA 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 storeRelational DBMSRelational DBMSSearch engineSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitehazelcast.comgoogle.github.io/­lovefieldhughestech.com.au/­products/­msqlsolr.apache.orgsphinxsearch.com
Technical documentationhazelcast.org/­imdg/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperHazelcastGoogleHughes TechnologiesApache Software FoundationSphinx Technologies Inc.
Initial release20082014199420062001
Current release5.3.6, November 20232.1.12, February 20174.4, October 20219.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial infofree licenses can be providedOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptCJavaC++
Server operating systemsAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.yes infothe object must implement a serialization strategynonoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageSQL-like query language infovia JavaScript builder patternA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
JavaScriptC
C++
Delphi
Java
Perl
PHP
Tcl
.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 proceduresyes infoEvent Listeners, Executor ServicesnonoJava pluginsno
Triggersyes infoEventsUsing read-only observersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapnonenoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmnoneEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes 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 infousing MemoryDBnoyes
User concepts infoAccess controlRole-based access controlnonoyesno

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More resources
HazelcastLovefieldmSQL infoMini SQLSolrSphinx
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