If you use MongoDB, then you may be feeling ecstatic right now. Why? Amazon Web Services (AWS) just released DocumentDB with MongoDB compatibility. Users who switch from MongoDB to DocumentDB can expect improved speed, scalability, and availability.
Today, we’re talking to Shawn Bice, vice president of non-relational databases at AWS, and Rahul Pathak, general manager of big data, data lakes, and blockchain at AWS . They share AWS’ overall database strategy and how to choose the best tool for what you want to build.
Some of the highlights of the show include:

Database Categories: Relational, key value, document, graph, in memory, ledger, and time series
AWS database strategy is to have the most popular and best APIs to sustain functionality, performance, and scale
Many database tools are available; pick based on use case and access pattern
Product recommendations feature highly connected data - who do you know who bought what and when?
Analytics Architecture: Use S3 as data lake, put in data via open-data format, and run multiple analyses using preferred tool at the same time on the same data
AWS offers Quantum Ledger Database (QLDB) and Managed Blockchain to address use case and need for blockchain
Authenticity of data is a concern with traditional databases; consider a database tool or service that does not allow data to be changed
Lake Formation lets customers set up, build, and secure data lakes in less time
DocumentDB: Made as simple as possible to improve customer experience
AWS Culture: Awareness and recognition that it takes many to conceive, build, launch, and grow a product - acknowledge every participant, including customers

Links:

Amazon DocumentDB
MongoDB
Amazon RDS
React
Aurora
re:Invent
DynamoDB
Amazon Neptune
Amazon Elasti-Cache
Amazon Quantum Ledger Database
Amazon Timestream
Amazon S3
Amazon EMR
Amazon Athena
Amazon Redshift
Amazon Managed Blockchain
Amazon EC2
Amazon Lake Formation
Perl
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