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DBMS > AnzoGraph DB vs. Apache Druid vs. GridDB vs. YottaDB

System Properties Comparison AnzoGraph DB vs. Apache Druid vs. GridDB vs. YottaDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Druid  Xexclude from comparisonGridDB  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable in-memory time series database optimized for IoT and Big DataA fast and solid embedded Key-value store
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Time Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitecambridgesemantics.com/­anzographdruid.apache.orggriddb.netyottadb.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdruid.apache.org/­docs/­latest/­designdocs.griddb.netyottadb.com/­resources/­documentation
DeveloperCambridge SemanticsApache Software Foundation and contributorsToshiba CorporationYottaDB, LLC
Initial release2018201220132001
Current release2.3, January 202129.0.1, April 20245.1, August 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache license v2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsLinuxLinux
OS X
Unix
LinuxDocker
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyes infoschema-less columns are supportedyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampno
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 indexesnoyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL for queryingSQL92, SQL-like TQL (Toshiba Query Language)by using the Octo plugin
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC++
Java
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infomanual/auto, time-basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes, via HDFS, S3 or other storage enginesSource-replica replicationyes
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 jobsno
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 graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container leveloptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databaseUsers and groups based on OS-security mechanisms
More information provided by the system vendor
AnzoGraph DBApache DruidGridDBYottaDB
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 DBApache DruidGridDBYottaDB
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