Episode Summary
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 CHAOSSEARCH
Episode Show Notes
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
- CHAOSSEARCH
.
