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DBMS > Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure SQL Database vs. Milvus

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure SQL Database vs. Milvus

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineDatabase 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 modelKey-value store
Wide column store
Graph DBMS
Key-value store
Relational DBMSVector DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitecloud.google.com/­bigtablewww.graphengine.ioazure.microsoft.com/­en-us/­products/­azure-sql/­databasemilvus.io
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­azure-sqlmilvus.io/­docs/­overview.md
DeveloperGoogleMicrosoftMicrosoft
Initial release2015201020102019
Current releaseV122.3.4, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen 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 language.NET and CC++C++, Go
Server operating systemshosted.NEThostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesVector, 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 indexesnoyesno
SQL infoSupport of SQLnonoyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesTransact SQLno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
Google Cloud BigtableGraph Engine infoformer name: TrinityMicrosoft 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 BigtableGraph Engine infoformer name: TrinityMicrosoft Azure SQL Database infoformerly SQL AzureMilvus
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