Azure
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AWS
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Storage (Blobs, Tables, Queues, Files)
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S3
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Virtual Machines
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EC2
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Autoscale
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AutoScaling
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Docker Virtual Machine Ext
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EC2 Container Service
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Blob Storage
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Elastic Block Storage
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HDInsight
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EMR
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Cloud Services Websites & Apps
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Elastic Beanstalk
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Backup
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Glacier
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Storsimple
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Storage Gateway
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Import export
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Import / export
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CDN
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Cloudfront
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SQL
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RDS
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DocumentDB
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DynamoDB
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Managed Cache (Redis)
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Elastic Cache
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Data Factory
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Data Pipeline / Glue
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Virtual Network
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VPC
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ExpressRoute
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Direct Connect
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Traffic Manager
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Route53
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Load Balancing
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Elastic Load Balancing
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Active Directory
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IAM
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Multi-Factor
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Multi-Factor
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Operational Insights
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CloudTrail
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Application Insights
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CloudWatch
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Event Hubs
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Kinesis
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Notification Hubs
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SNS
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Key Vault
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Key Management Service
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Resource Manager
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Cloud Formation
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API Management
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API Gateway
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Automation
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Opsworks
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Batch
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SQS
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Search
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CloudSearch
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Service Bus
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SWF
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Stream Analytics
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Kinesis
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Biztalk
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SES
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Machine Learning (preview)
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Machine Learning
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Functions
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Lambda
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Gets more expensive as you use more on the 'you only pay for what you use model' (especially Linux instances)
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Less expensive as you use more on the 'you only pay for what you use model'
(has plenty of linux options and windows options are priced the same as azure)
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Generally, slower in services
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Generally, faster in services
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Very confusing naming for services some of which are not even services but just reused applications in the cloud
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Service names are distinguishable and clear
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Azure charges by the minute
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AWS charges by the hour
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ML and data analytics options are not that great.
Azure only has cosmodb, hdinsight, event hub, storage, its AI services are not great either, tight coupling to azure windows services, not ideal for data science work - with azure for non-windows type work is not seamless. CosmoDB is a strong option –it supports documentdb, mongodb, property graph, cassandra, table – not perfect but ok.
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Data Pipeline
Kinesis
S3
Deep Learning library support + AMIs,
Support for GPU instances
More flexible DBs, But no multi-model option, Redshift, EMR (supports spark, flink, presto, hbase, hive, pig), glue, athena, elasticsearch, cloudsearch, clustering is easier for linux machines (can you see running hadoop on windows?), AWS has neptune that supports property graphs, rdf, sparql,
tinkerpop. |
azure vs aws service mappings
