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

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

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMicrosoft 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 modelTime Series DBMSRelational DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­spotify/­heroicwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.orgsphinxsearch.com
Technical documentationspotify.github.io/­heroicdeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperSpotifyMicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release2014199220062001
Current release1902 (16.0.11328.20222), March 20199.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial 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 languageJavaC++JavaC++
Server operating systemsWindows 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 dateyesyesyes 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 Elasticsearchyesyes 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 methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC
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 proceduresnoyes infosince Access 2010 using the ACE-engineJava pluginsno
Triggersnoyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes 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.noyes
User concepts infoAccess controlno infoa simple user-level security was built in till version Access 2003yesno

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More resources
HeroicMicrosoft AccessSolrSphinx
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