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DBMS > EsgynDB vs. Lovefield vs. Solr vs. Vitess vs. Yaacomo

System Properties Comparison EsgynDB vs. Lovefield vs. Solr vs. Vitess vs. Yaacomo

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonLovefield  Xexclude from comparisonSolr  Xexclude from comparisonVitess  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEmbeddable relational database for web apps written in pure JavaScriptA widely used distributed, scalable search engine based on Apache LuceneScalable, distributed, cloud-native DBMS, extending MySQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.esgyn.cngoogle.github.io/­lovefieldsolr.apache.orgvitess.ioyaacomo.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.htmlvitess.io/­docs
DeveloperEsgynGoogleApache Software FoundationThe Linux Foundation, PlanetScaleQ2WEB GmbH
Initial release20152014200620132009
Current release2.1.12, February 20179.6.1, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaScriptJavaGo
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Android
Linux
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesyes
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 indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL-like query language infovia JavaScript builder patternSolr Parallel SQL Interfaceyes infowith proprietary extensionsyes
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored ProceduresnoJava pluginsyes infoproprietary syntax
TriggersnoUsing read-only observersyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneyesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integrityyesyesnoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDByesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyesUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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More resources
EsgynDBLovefieldSolrVitessYaacomo
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