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DBMS > AgensGraph vs. Linter vs. Quasardb vs. Solr vs. Transwarp StellarDB

System Properties Comparison AgensGraph vs. Linter vs. Quasardb vs. Solr vs. Transwarp StellarDB

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonLinter  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLRDBMS for high security requirementsDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache LuceneA distributed graph DBMS built for enterprise-level graph applications
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSTime Series DBMSSearch engineGraph DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.00
Rank#383  Overall
#39  Graph DBMS
Websitebitnine.net/­agensgraphlinter.ruquasar.aisolr.apache.orgwww.transwarp.cn/­en/­product/­stellardb
Technical documentationbitnine.net/­documentationdoc.quasar.ai/­mastersolr.apache.org/­resources.html
DeveloperBitnine Global Inc.relex.ruquasardbApache Software FoundationTranswarp
Initial release2016199020092006
Current release2.1, December 20183.14.1, January 20249.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2commercial
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 languageCC and C++C++Java
Server operating systemsLinux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
BSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedepending on used data modelyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesyesyes infowith tagsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesSQL-like query languageSolr Parallel SQL InterfaceSQL-like query language
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP APIJava API
RESTful HTTP/JSON API
OpenCypher
Supported programming languagesC
Java
JavaScript
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyes infoproprietary syntax with the possibility to convert from PL/SQLnoJava plugins
Triggersnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneSharding infoconsistent hashingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailyesyes

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More resources
AgensGraphLinterQuasardbSolrTranswarp StellarDB
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