Tour of Data Platforms as a Service - Pythian's Christo Kutrovsky at Cloud Expo 2016
Presented by Pythian's Christo Kutrovsky, with supporting material created by Pythian's Warner Chaves. With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right provider and with the proper expectations. In this session we'll compare the NoSQL and SQL offerings from AWS, Microsoft Azure and Google Cloud, their similarities, differences and use cases for each one based on our own client projects.
Tour of Data Platforms as a Service - Pythian's Christo Kutrovsky at Cloud Expo 2016
- 1. Tour of Data Platforms as a Service Presented by Christo Kutrovsky of Pythian, with support of Warner Chaves of Pythian, at Cloud Expo 2016
- 5. Scope
- 6. The Corollas You know what you¡¯re getting, what to expect.
- 8. Amazon RDS What it¡¯s great for, and what to watch out for.
- 10. Azure SQL Database What it¡¯s great for, and what to watch out for.
- 11. About Oracle Database in the Cloud
- 12. Oracle Database in the Cloud What it¡¯s great for, ad what to watch out for.
- 13. Formula 1 Fit for one purpose, not all the amenities.
- 15. Amazon DynamoDb What it¡¯s great for, and what to watch out for.
- 17. Azure DocumentDb What it¡¯s great for, and what to watch out for.
- 18. The 18 Wheelers Heavy load of structured data.
- 20. Amazon Redshift What it¡¯s great for, and what to watch out for.
- 21. About Azure SQL Data Warehouse
- 22. Azure SQL Data Warehouse What it¡¯s great for, and what to watch out for.
- 24. Oracle Exadata Cloud What it¡¯s great for, and what to watch out for.
- 25. The Container Ships Can carry everything, in any shape or form.
- 27. Google Bigquery What it¡¯s great for, and what to watch out for.
- 28. About Azure Data Lake
- 29. Azure Data Lake What it¡¯s great for, and what to watch out for.
- 31. Thank you!