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DBMS > AgensGraph vs. Apache IoTDB vs. Quasardb vs. Solr vs. Spark SQL

System Properties Comparison AgensGraph vs. Apache IoTDB vs. Quasardb vs. Solr vs. Spark SQL

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache IoTDB  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
Relational DBMS
Time Series DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebitnine.net/­agensgraphiotdb.apache.orgquasar.aisolr.apache.orgspark.apache.org/­sql
Technical documentationbitnine.net/­documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldoc.quasar.ai/­mastersolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBitnine Global Inc.Apache Software FoundationquasardbApache Software FoundationApache Software Foundation
Initial release20162018200920062014
Current release2.1, December 20181.1.0, April 20233.14.1, January 20249.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2Open Source infoApache 2.0
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 languageCJavaC++JavaScala
Server operating systemsLinux
OS X
Windows
All OS with a Java VM (>= 1.8)BSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemedepending on used data modelyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes 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.nononoyesno
Secondary indexesyesyesyes infowith tagsyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesSQL-like query languageSQL-like query languageSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
JDBC
Native API
HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
C
C#
C++
Go
Java
Python
Scala
.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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesnoJava pluginsno
Triggersnoyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoconsistent hashingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication with selectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkwith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic lockingno
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.noyesyes infoTransient modeyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesCryptographically strong user authentication and audit trailyesno

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More resources
AgensGraphApache IoTDBQuasardbSolrSpark SQL
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