Data lakes store raw, unprocessed data for flexible exploration, real-time analysis, and to disburden data warehousing. Data warehouses organize structured data for business reports, quick access to specific information, and analyzing historical trends. Choosing between them depends on data types, goals, budget, and skills, as there is no one-size-fits-all solution in data storage.
Tag: AWS
Create AWS Athena View Using AWS CDK
Athena Views!Sounds like SQL Views, correct? To some extent they are, means athena view is also a logical table and it does not hold any physical data.Good news is that manually, it is created similarly as SQL view, but what if you need to create it programmatically? In today's era most of the companies follow … Continue reading Create AWS Athena View Using AWS CDK
Trigger AWS Lambda with AWS SNS using Python
Applications rely on the advantages of serverless technologies and message delivery is a critical part of that. In distributed applications reliable messaging plays a key role as this allow them to communicate with each other to improve their availability and scalability. You must already know the two methods of messaging- Synchronous - Sender expects an … Continue reading Trigger AWS Lambda with AWS SNS using Python
Trigger AWS Lambda with AWS SQS using Python
All the developers who have used AWS SQS earlier must have experienced the hassle of polling to receive messages from queue. Whether you use short polling or long polling, it was always a tough thing to handle the process of message retrieval. And then, AWS announced that SQS is available as AWS Lambda event source. … Continue reading Trigger AWS Lambda with AWS SQS using Python
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