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DBMS > GridDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

System Properties Comparison GridDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSVector DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegriddb.netazure.microsoft.com/­services/­synapse-analyticsmilvus.iospark.apache.org/­sql
Technical documentationdocs.griddb.netdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperToshiba CorporationMicrosoftApache Software Foundation
Initial release2013201620192014
Current release5.1, August 20222.3.4, January 20243.5.0 ( 2.13), September 2023
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 2.0Open Source infoApache 2.0
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++C++, GoScala
Server operating systemsLinuxhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesyesyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLnono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
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 integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDnono
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.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseyesRole based access control and fine grained access rightsno
More information provided by the system vendor
GridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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 Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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