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DBMS > Lovefield vs. Stardog vs. Trafodion vs. Vitess

System Properties Comparison Lovefield vs. Stardog vs. Trafodion vs. Vitess

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonStardog  Xexclude from comparisonTrafodion  Xexclude from comparisonVitess  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEmbeddable relational database for web apps written in pure JavaScriptEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTransactional SQL-on-Hadoop DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websitegoogle.github.io/­lovefieldwww.stardog.comtrafodion.apache.orgvitess.io
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.stardog.comtrafodion.apache.org/­documentation.htmlvitess.io/­docs
DeveloperGoogleStardog-UnionApache Software Foundation, originally developed by HPThe Linux Foundation, PlanetScale
Initial release2014201020142013
Current release2.1.12, February 20177.3.0, May 20202.3.0, February 201915.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache 2.0Open 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaC++, JavaGo
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
macOS
Windows
LinuxDocker
Linux
macOS
Data schemeyesschema-free and OWL/RDFS-schema supportyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono infoImport/export of XML data possibleno
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialyesyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternYes, compatible with all major SQL variants through dedicated BI/SQL Serveryesyes infowith proprietary extensions
APIs and other access methodsGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJavaScript.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetAda
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 proceduresnouser defined functions and aggregates, HTTP Server extensions in JavaJava Stored Proceduresyes infoproprietary syntax
TriggersUsing read-only observersyes infovia event handlersnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication in HA-Clusteryes, via HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in HA-ClusterImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes inforelationships in graphsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes, 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.yes infousing MemoryDByesnoyes
User concepts infoAccess controlnoAccess rights for users and rolesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
LovefieldStardogTrafodionVitess
Recent citations in the news

Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
20 May 2024, InfoQ.com

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

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provided by Google News



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