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DBMS > AllegroGraph vs. Apache Phoenix vs. Google BigQuery vs. Hive

System Properties Comparison AllegroGraph vs. Apache Phoenix vs. Google BigQuery vs. Hive

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHive  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA scale-out RDBMS with evolutionary schema built on Apache HBaseLarge scale data warehouse service with append-only tablesdata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Websiteallegrograph.comphoenix.apache.orgcloud.google.com/­bigqueryhive.apache.org
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlphoenix.apache.orgcloud.google.com/­bigquery/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperFranz Inc.Apache Software FoundationGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2004201420102012
Current release8.0, December 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen 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

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Implementation languageJavaJava
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows
hostedAll OS with a Java VM
Data schemeyes infoRDF schemasyes infolate-bound, schema-on-read capabilitiesyesyes
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.no infobulk load of XML files possiblenono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languageyesyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
JDBCRESTful HTTP/JSON APIJDBC
ODBC
Thrift
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functionsuser defined functions infoin JavaScriptyes infouser defined functions and integration of map-reduce
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoSince BigQuery is designed for querying datano
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.noyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
AllegroGraphApache PhoenixGoogle BigQueryHive
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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