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DBMS > AnzoGraph DB vs. Apache Phoenix vs. BigObject vs. GridDB

System Properties Comparison AnzoGraph DB vs. Apache Phoenix vs. BigObject vs. GridDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonBigObject  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic DBMS for real-time computations and queriesScalable in-memory time series database optimized for IoT and Big Data
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitecambridgesemantics.com/­anzographphoenix.apache.orgbigobject.iogriddb.net
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmphoenix.apache.orgdocs.bigobject.iodocs.griddb.net
DeveloperCambridge SemanticsApache Software FoundationBigObject, Inc.Toshiba Corporation
Initial release2018201420152013
Current release2.3, January 20215.0-HBase2, July 2018 and 4.15-HBase1, December 20195.1, August 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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 languageJavaC++
Server operating systemsLinuxLinux
Unix
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBCfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsLuano
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingHadoop integrationnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual ConsistencynoneImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno infonot needed in graphsnoyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/write lock on objects (tables, trees)yes
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.yesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users can be defined per database
More information provided by the system vendor
AnzoGraph DBApache PhoenixBigObjectGridDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
AnzoGraph DBApache PhoenixBigObjectGridDB
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