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DBMS > Amazon DynamoDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Milvus

System Properties Comparison Amazon DynamoDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Milvus

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Wide Column Store for rapid development using massive semi-structured datasetsA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Wide column storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.78
Rank#103  Overall
#4  Vector DBMS
Websiteaws.amazon.com/­dynamodbcloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tablesmilvus.io
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­bigtable/­docsmilvus.io/­docs/­overview.md
DeveloperAmazonGoogleMicrosoft
Initial release2012201520122019
Current release2.4.4, May 2024
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercialOpen 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 languageC++, Go
Server operating systemshostedhostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesVector, 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.nonono
Secondary indexesyesnonono
SQL infoSupport of SQLnononono
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIRESTful HTTP API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononono
Triggersyes infoby integration with AWS Lambdanonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate 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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionAtomic single-row operationsoptimistic lockingno
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 controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesRole based access control and fine grained access rights
More information provided by the system vendor
Amazon DynamoDBGoogle Cloud BigtableMicrosoft Azure Table StorageMilvus
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
Amazon DynamoDBGoogle Cloud BigtableMicrosoft Azure Table StorageMilvus
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