Databases are the core of most applications, whether transactional or analytical. In recent years the selection of database products has exploded, making the critical decision of which engine(s) to use even more difficult. In this episode Tanya Bragin shares her experiences as a product manager for two major vendors and the lessons that she has learned about how teams should approach the process of tool selection.
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- Your host is Tobias Macey and today I'm interviewing Tanya Bragin about her views on the database products market
- How did you get involved in the area of data management?
- What are the aspects of the database market that keep you interested as a VP of product?
- How have your experiences at Elastic informed your current work at Clickhouse?
- What are the main product categories for databases today?
- What are the industry trends that have the most impact on the development and growth of different product categories?
- Which categories do you see growing the fastest?
- When a team is selecting a database technology for a given task, what are the types of questions that they should be asking?
- Transactional engines like Postgres, SQL Server, Oracle, etc. were long used as analytical databases as well. What is driving the broad adoption of columnar stores as a separate environment from transactional systems?
- What are the inefficiencies/complexities that this introduces?
- How can the database engine used for analytical systems work more closely with the transactional systems?
- When building analytical systems there are numerous moving parts with intricate dependencies. What is the role of the database in simplifying observability of these applications?
- What are the most interesting, innovative, or unexpected ways that you have seen Clickhouse used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on database products?
- What are your prodictions for the future of the database market?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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