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

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

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase 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 modelGraph DBMS
Relational DBMS
Document storeRelational DBMSVector DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasemilvus.io
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlmilvus.io/­docs/­overview.md
DeveloperBitnine Global Inc.GoogleMicrosoft
Initial release2016200820102019
Current release2.1, December 2018V122.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
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 systemsLinux
OS X
Windows
hostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemedepending on used data modelschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesVector, 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 SQLyesSQL-like query language (GQL)yesno
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesusing Google App EngineTransact SQLno
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integrityyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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
AgensGraphGoogle Cloud DatastoreMicrosoft 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
AgensGraphGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureMilvus
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