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DBMS > AnzoGraph DB vs. Drizzle vs. EsgynDB vs. GridDB

System Properties Comparison AnzoGraph DB vs. Drizzle vs. EsgynDB vs. GridDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable in-memory time series database optimized for IoT and Big Data
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSTime 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitecambridgesemantics.com/­anzographwww.esgyn.cngriddb.net
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.griddb.net
DeveloperCambridge SemanticsDrizzle project, originally started by Brian AkerEsgynToshiba Corporation
Initial release2018200820152013
Current release2.3, January 20217.2.4, September 20125.1, August 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoGNU GPLcommercialOpen 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

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Implementation languageC++C++, JavaC++
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxLinux
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyes
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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infowith proprietary extensionsyesSQL92, 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
JDBCADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava Stored Proceduresno
Triggersnono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyesConnector 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 ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno infonot needed in graphsyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at container level
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users can be defined per database
More information provided by the system vendor
AnzoGraph DBDrizzleEsgynDBGridDB
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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AnzoGraph DBDrizzleEsgynDBGridDB
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Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

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8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

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