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DBMS > GridDB vs. Ingres vs. InterSystems IRIS vs. Quasardb vs. Vertica

System Properties Comparison GridDB vs. Ingres vs. InterSystems IRIS vs. Quasardb vs. Vertica

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonIngres  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonQuasardb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataWell established RDBMSA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityDistributed, high-performance timeseries databaseCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegriddb.netwww.actian.com/­databases/­ingreswww.intersystems.com/­products/­intersystems-irisquasar.aiwww.vertica.com
Technical documentationdocs.griddb.netdocs.actian.com/­ingresdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdoc.quasar.ai/­mastervertica.com/­documentation
DeveloperToshiba CorporationActian CorporationInterSystemsquasardbOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20131974 infooriginally developed at University Berkely in early 1970s201820092005
Current release5.1, August 202211.2, May 20222023.3, June 20233.14.1, January 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++C++
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
AIX
Linux
macOS
Ubuntu
Windows
BSD
Linux
OS X
Windows
Linux
Data schemeyesyesdepending on used data modelschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes infointeger and binaryyes
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.nono infobut tools for importing/exporting data from/to XML-files availableyesnono
Secondary indexesyesyesyesyes infowith tagsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesyesSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
RESTful HTTP API
HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingSharding infoconsistent hashinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationIngres ReplicatorSource-replica replicationSource-replica replication with selectable replication factorMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonowith Hadoop integrationno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes infoTransient modeno
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardyesCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GridDBIngresInterSystems IRISQuasardbVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
GridDBIngresInterSystems IRISQuasardbVertica infoOpenText™ Vertica™
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