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DBMS > AnzoGraph DB vs. GridDB vs. IRONdb vs. Prometheus

System Properties Comparison AnzoGraph DB vs. GridDB vs. IRONdb vs. Prometheus

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGridDB  Xexclude from comparisonIRONdb  Xexclude from comparisonPrometheus  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it 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 virtualizationScalable in-memory time series database optimized for IoT and Big DataA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen-source Time Series DBMS and monitoring system
Primary database modelGraph DBMS
RDF store
Time Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitecambridgesemantics.com/­anzographgriddb.netwww.circonus.com/solutions/time-series-database/prometheus.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.griddb.netdocs.circonus.com/irondb/category/getting-startedprometheus.io/­docs
DeveloperCambridge SemanticsToshiba CorporationCirconus LLC.
Initial release2018201320172015
Current release2.3, January 20215.1, August 2022V0.10.20, January 2018
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0
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++C and C++Go
Server operating systemsLinuxLinuxLinuxLinux
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infotext, numeric, histogramsNumeric data only
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 infoImport of XML data possible
Secondary indexesnoyesnono
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP APIRESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes, in Luano
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-replica replicationconfigurable replication factor, datacenter awareyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate consistency within container, eventual consistency across containersImmediate consistency per node, eventual consistency across nodesnone
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnono
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.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databasenono
More information provided by the system vendor
AnzoGraph DBGridDBIRONdbPrometheus
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 DBGridDBIRONdbPrometheus
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