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DBMS > AnzoGraph DB vs. BigObject vs. EventStoreDB vs. GridDB

System Properties Comparison AnzoGraph DB vs. BigObject vs. EventStoreDB vs. GridDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonBigObject  Xexclude from comparisonEventStoreDB  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 virtualizationAnalytic DBMS for real-time computations and queriesIndustrial-strength, open-source database solution built from the ground up for event sourcing.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedEvent StoreTime 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.10
Rank#179  Overall
#1  Event Stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitecambridgesemantics.com/­anzographbigobject.iowww.eventstore.comgriddb.net
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.bigobject.iodevelopers.eventstore.comdocs.griddb.net
DeveloperCambridge SemanticsBigObject, Inc.Event Store LimitedToshiba Corporation
Initial release2018201520122013
Current release2.3, January 202121.2, February 20215.1, August 2022
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infofree community edition availableOpen SourceOpen 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 languageC++
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Windows
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyesyes
Typing infopredefined data types such as float or dateyesyes 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 indexesnoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-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
fluentd
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesLuano
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusternoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoConnector 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-ClusternoneImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno infonot needed in graphsyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users can be defined per database
More information provided by the system vendor
AnzoGraph DBBigObjectEventStoreDBGridDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AnzoGraph DBBigObjectEventStoreDBGridDB
Recent citations in the news

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

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

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

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

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19 August 2022, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3 December 2019, global.toshiba

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