Both Managed and PaaS services provide advantages over First generation big data platforms , through their minimized requirements for operations , management and administration . The rapid pace of innovation and constant stream of new features from AWS , Google and Azure ( Figure 2 ) only amplify the benefits with new features and capabilities , deployed at scale and often available for minimal cost uptick .
|
AWS |
Azure |
Google |
Presentation |
QuickSight |
PowerBI |
Cloud DataLab |
Streaming Data |
Kinesis Firehose , Kinesis Streams |
Stream Analytics |
Cloud Dataflow |
AI , Machine Learning |
Rekognition , Machine Learning , Polly , Lex |
Azure Machine Learning |
Cloud ML , Vision API , Prediction API |
Query , Analytics & Processing |
EMR , Aurora , Athena , DynamoDB , Kinesis Analytics |
Azure SQL , HD Insight |
BigQuery |
Storage |
S3 |
Azure Storage |
Cloud Storage |
Figure 2 - Second Generation Capabilities by Platform
First generation big data platforms made big data analysis a reality . But if you are an owner of a First generation big data platform , and you find yourself mired with the day to day burden of operations and stability maintenance , at the expense of supporting data integration and analysis , then consider public cloud . Through the use of managed and PaaS services , your data analysis team can focus on service consumption and quality of results , while operations teams can focus on ensuring best practices and user satisfaction .
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