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DBMS > Google Cloud Datastore vs. Machbase Neo vs. Microsoft Azure SQL Database vs. Milvus

System Properties Comparison Google Cloud Datastore vs. Machbase Neo vs. Microsoft Azure SQL Database vs. Milvus

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTimeSeries DBMS for AIoT and BigDataDatabase as a Service offering with high compatibility to Microsoft SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument storeTime Series DBMSRelational DBMSVector DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitecloud.google.com/­datastoremachbase.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasemilvus.io
Technical documentationcloud.google.com/­datastore/­docsmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­azure-sqlmilvus.io/­docs/­overview.md
DeveloperGoogleMachbaseMicrosoft
Initial release2008201320102019
Current releaseV8.0, August 2023V122.3.4, January 2024
License infoCommercial or Open Sourcecommercialcommercial infofree test version availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
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 languageCC++C++, Go
Server operating systemshostedLinux
macOS
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesVector, Numeric and String
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App EnginenoTransact SQLno
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factoryes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infovolatile and lookup tableyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
Google Cloud DatastoreMachbase Neo infoFormer name was InfinifluxMicrosoft Azure SQL Database infoformerly SQL AzureMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Google Cloud DatastoreMachbase Neo infoFormer name was InfinifluxMicrosoft Azure SQL Database infoformerly SQL AzureMilvus
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