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DBMS > AgensGraph vs. Apache Phoenix vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison AgensGraph vs. Apache Phoenix vs. Microsoft Azure Table Storage vs. Solr

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Phoenix  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLA scale-out RDBMS with evolutionary schema built on Apache HBaseA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSWide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitebitnine.net/­agensgraphphoenix.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationbitnine.net/­documentationphoenix.apache.orgsolr.apache.org/­resources.html
DeveloperBitnine Global Inc.Apache Software FoundationMicrosoftApache Software Foundation
Initial release2016201420122006
Current release2.1, December 20185.0-HBase2, July 2018 and 4.15-HBase1, December 20199.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedepending on used data modelyes infolate-bound, schema-on-read capabilitiesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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 indexesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesnoSolr Parallel SQL Interface
APIs and other access methodsCypher Query Language
JDBC
JDBCRESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesC
Java
JavaScript
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnoJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights based on private key authentication or shared access signaturesyes

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More resources
AgensGraphApache PhoenixMicrosoft Azure Table StorageSolr
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