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DBMS > GridDB vs. Microsoft Azure Table Storage vs. Milvus vs. Netezza

System Properties Comparison GridDB vs. Microsoft Azure Table Storage vs. Milvus vs. Netezza

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMilvus  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA Wide Column Store for rapid development using massive semi-structured datasetsA DBMS designed for efficient storage of vector data and vector similarity searchesData warehouse and analytics appliance part of IBM PureSystems
Primary database modelTime Series DBMSWide column storeVector DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitegriddb.netazure.microsoft.com/­en-us/­services/­storage/­tablesmilvus.iowww.ibm.com/­products/­netezza
Technical documentationdocs.griddb.netmilvus.io/­docs/­overview.md
DeveloperToshiba CorporationMicrosoftIBM
Initial release2013201220192000
Current release5.1, August 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2.0commercial
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++C++, Go
Server operating systemsLinuxhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux infoincluded in appliance
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesVector, Numeric and Stringyes
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 indexesyesnonoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nonoyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnononoyes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container leveloptimistic lockingnoACID
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.yesnoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights based on private key authentication or shared access signaturesRole based access control and fine grained access rightsUsers with fine-grained authorization concept
More information provided by the system vendor
GridDBMicrosoft Azure Table StorageMilvusNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsGitHub trending repository
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
GridDBMicrosoft Azure Table StorageMilvusNetezza infoAlso called PureData System for Analytics by IBM
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