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DBMS > GridDB vs. Microsoft Azure SQL Database vs. Netezza vs. RavenDB

System Properties Comparison GridDB vs. Microsoft Azure SQL Database vs. Netezza vs. RavenDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataDatabase as a Service offering with high compatibility to Microsoft SQL ServerData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
Document store
Graph DBMS
Spatial DBMS
Graph 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
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitegriddb.netazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.ibm.com/­products/­netezzaravendb.net
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­azure-sqlravendb.net/­docs
DeveloperToshiba CorporationMicrosoftIBMHibernating Rhinos
Initial release2013201020002010
Current release5.1, August 2022V125.4, July 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C#
Server operating systemsLinuxhostedLinux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoTransact SQLyesyes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availableSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDACID, Cluster-wide transaction available
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.yes
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAuthorization levels configured per client per database
More information provided by the system vendor
GridDBMicrosoft Azure SQL Database infoformerly SQL AzureNetezza infoAlso called PureData System for Analytics by IBMRavenDB
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
GridDBMicrosoft Azure SQL Database infoformerly SQL AzureNetezza infoAlso called PureData System for Analytics by IBMRavenDB
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