Relational SQL databases remain the winner when it comes to optimal and structured data storage and management. However, as data storage needs become more complex, especially with the rise of AI, NoSQL databases are making waves. NoSQL (Not-Only-SQL) is a powerful alternative, excelling at handling large volumes of unstructured, non-relational data and offering flexible data structures for ever-evolving schemas. In this session, we will explore the basics and core concepts of different types of NoSQL databases, such as document stores, key-value stores, and graph databases. We’ll discuss the ideal use cases and best practices for each store, their unique strengths, and how they compare to traditional relational databases in various scenarios. We will also cover practical examples, such as using graph databases for more efficient retrieval in AI applications, or leveraging document stores for storing and querying raw logs. By the end of the session, attendees will be equipped with the knowledge required to implement NoSQL data storage in Azure, as well as being able to make informed decisions about when and where to implement NoSQL databases. While NoSQL is not always the answer, choosing the right data store will always ensure scalability and performance for your data solutions.

Managing hybrid environments across clouds, domains, and database platforms presents significant challenges in observability, scalability, and maintaining estate health. In this session, Peter Birch from Markel shares real-world insights in managing large database estates and its challenges, detailing how they leveraged Redgate Monitor to ensure visibility, optimize performance, and mitigate risks. Learn how to navigate the demands of hybrid infrastructure and cloud migrations, implement best practices for observability at scale, and overcome pitfalls in managing a diverse database estate.