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 seriesAWS database strategy is to have the most popular and best APIs to sustain functionality, performance, and scaleMany database tools are available; pick based on use case and access patternProduct 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 blockchainAuthenticity of data is a concern with traditional databases; consider a database tool or service that does not allow data to be changedLake Formation lets customers set up, build, and secure data lakes in less timeDocumentDB: Made as simple as possible to improve customer experienceAWS Culture: Awareness and recognition that it takes many to conceive, build, launch, and grow a product - acknowledge every participant, including customersAmazon DocumentDBMongoDBAmazon RDSReactAurorare:InventDynamoDBAmazon NeptuneAmazon Elasti-CacheAmazon Quantum Ledger DatabaseAmazon TimestreamAmazon S3Amazon EMRAmazon AthenaAmazon RedshiftAmazon Managed BlockchainAmazon EC2Amazon Lake FormationPerlCHAOSSEARCH.