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DBMS > DataFS vs. Solr vs. Spark SQL vs. TimescaleDB vs. TinkerGraph

System Properties Comparison DataFS vs. Solr vs. Spark SQL vs. TimescaleDB vs. TinkerGraph

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTinkerGraph  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.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelObject oriented DBMSSearch engineRelational DBMSTime Series DBMSGraph DBMS
Secondary database modelsGraph DBMSSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitenewdatabase.comsolr.apache.orgspark.apache.org/­sqlwww.timescale.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdev.mobiland.com/­Overview.xspsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperMobiland AGApache Software FoundationApache Software FoundationTimescale
Initial release20182006201420172009
Current release1.1.263, October 20229.6.0, April 20243.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaCJava
Server operating systemsWindowsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yes infoDynamic Fields enables on-the-fly addition of new fieldsyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.noyesnoyesno
Secondary indexesnoyes infoAll search fields are automatically indexednoyesno
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxno
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
TinkerPop 3
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Groovy
Java
Server-side scripts infoStored proceduresJava pluginsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersno, except callback-events from server when changes happenedyes infoUser configurable commands triggered on index changesnoyesno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyesnonoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlWindows-Profileyesnofine grained access rights according to SQL-standardno

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More resources
DataFSSolrSpark SQLTimescaleDBTinkerGraph
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