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DBMS > DataFS vs. Datomic vs. Solr vs. Vitess

System Properties Comparison DataFS vs. Datomic vs. Solr vs. Vitess

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonDatomic  Xexclude from comparisonSolr  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA widely used distributed, scalable search engine based on Apache LuceneScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelObject oriented DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsGraph DBMSSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#360  Overall
#18  Object oriented DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitenewdatabase.comwww.datomic.comsolr.apache.orgvitess.io
Technical documentationdev.mobiland.com/­Overview.xspdocs.datomic.comsolr.apache.org/­resources.htmlvitess.io/­docs
DeveloperMobiland AGCognitectApache Software FoundationThe Linux Foundation, PlanetScale
Initial release2018201220062013
Current release1.1.263, October 20221.0.7075, December 20239.6.1, May 202415.0.2, December 2022
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaGo
Server operating systemsWindowsAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes 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 typingyes
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
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceyes infowith proprietary extensions
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APIJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
Clojure
Java
.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 proceduresyes infoTransaction FunctionsJava pluginsyes infoproprietary syntax
Triggersno, except callback-events from server when changes happenedBy using transaction functionsyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesMulti-source replication
Source-replica replication
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 systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlWindows-ProfilenoyesUsers with fine-grained authorization concept infono user groups or roles

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