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DBMS > AnzoGraph DB vs. Apache Impala vs. GridDB

System Properties Comparison AnzoGraph DB vs. Apache Impala vs. GridDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Impala  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 HadoopScalable in-memory time series database optimized for IoT and Big Data
Primary database modelGraph DBMS
RDF store
Relational DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Websitecambridgesemantics.com/­anzographimpala.apache.orggriddb.net
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmimpala.apache.org/­impala-docs.htmldocs.griddb.net
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba Corporation
Initial release201820132013
Current release2.3, January 20214.1.0, June 20225.1, August 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2Open 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 servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxLinuxLinux
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
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
All languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reduceno
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infoquery execution via MapReduceConnector 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-ClusterEventual 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 level
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per database
More information provided by the system vendor
AnzoGraph DBApache ImpalaGridDB
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 ImpalaGridDB
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

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

How Knowledge Graphs Automate Data Preparation
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General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ...
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Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

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3 December 2019, global.toshiba

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