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DBMS > Google Cloud Datastore vs. IBM Cloudant vs. Microsoft Azure Synapse Analytics vs. Milvus

System Properties Comparison Google Cloud Datastore vs. IBM Cloudant vs. Microsoft Azure Synapse Analytics vs. Milvus

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering based on Apache CouchDBElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument storeDocument storeRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score2.68
Rank#106  Overall
#20  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­cloudantazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationcloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudantdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Microsoft
Initial release2008201020162019
Current release2.3.4, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
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 languageErlangC++C++, Go
Server operating systemshostedhostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details herenoyesVector, 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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)noyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App EngineView functions (Map-Reduce) in JavaScriptTransact SQLno
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
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.Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a document possibleACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes
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 controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseyesRole based access control and fine grained access rights
More information provided by the system vendor
Google Cloud DatastoreIBM CloudantMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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 DatastoreIBM CloudantMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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