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DBMS > Heroic vs. LokiJS vs. Spark SQL vs. Sphinx

System Properties Comparison Heroic vs. LokiJS vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonLokiJS  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchIn-memory JavaScript DBMSSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument storeRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.43
Rank#264  Overall
#42  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­spotify/­heroicgithub.com/­techfort/­LokiJSspark.apache.org/­sqlsphinxsearch.com
Technical documentationspotify.github.io/­heroictechfort.github.io/­LokiJSspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperSpotifyApache Software FoundationSphinx Technologies Inc.
Initial release2014201420142001
Current release3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0Open 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 languageJavaJavaScriptScalaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesno
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.nonono
Secondary indexesyes infovia Elasticsearchyes infovia viewsnoyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JavaScript APIJDBC
ODBC
Proprietary protocol
Supported programming languagesJavaScriptJava
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoView functions in JavaScriptnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single collection possiblenono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yesyes 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.noyesno
User concepts infoAccess controlnonono

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HeroicLokiJSSpark SQLSphinx
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