Beyond Relational with Traditional Databases – Working with JSON, Spatial data and Full-Text Search
Relational databases are great for storing relational data and performing crud operations, but did you know that you can go beyond basic relational queries with RDBMS? Do you need to store and query non-structured data in JSON documents? Or perhaps you want to store spatial data and find the nearest points of interest to a given location? What if you have a lot of records and need to sift through them and run full-text search queries? Are you required to keep historical information about data that has been modified or maybe even deleted? If you answered Yes to any of the above questions, this is the talk you do not want to miss.
In this session, you will see how to achieve each of the above goals with Microsoft SQL Server or PostgreSQL. Specifically, I will step through and show how you can store and manipulate JSON documents, how to use PostGIS for spatial data, utilize temporal tables to keep your data’s complete history and work with full-text search.
Developers working with PostgreSQL or Microsoft SQL Server will learn how to store data in JSON columns and how easily you can drill into the JSON data with JSON Functions. You will see how to filter and sort results based on elements of the JSON document, project elements from JSON, and update the JSON document. I will show how to store spatial data with Microsoft SQL Server/PostgreSQL and run spatial queries. I will also demonstrate how easy it is to run full-text search queries to find exact or partial matches for your search term and how to set up full-text query indexes. Furthermore, you will see how temporal tables can store all the historical data and how straightforward it is to query for historical records.
Join me for a demo-rich session and learn about relational database features that you can apply right after the session.