Slick 3: Functional Relational Mapping for Mere Mortals Part 2: Querying data

Last week we learnt the basics of Slick library. We started with a general introduction of Slick, then covered how to define a table definition, custom mappers, and perform insert queries. Today, we will learn how to perform select queries with Slick. Slick allows you to work with database tables in the same way as you work with Scala collections. This means that you can use methods like map, filter, sort, etc. to process data in your table.

You can read the full blog here https://github.com/shekhargulati/52-technologies-in-2016/blob/master/05-slick/README.md

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Slick: Functional Relational Mapping for Mere Mortals Part 1

Welcome to the fourth blog of 52-technologies-in-2016 blog series. Today, we will get started with Slick. Slick(Scala Language-Integrated Connection Kit) is a powerful Scala library to work with relational databases. Slick is not an ORM library. It bases its implementation on functional programming and does not hide database behind an ORM layer giving you full control over when a database access should happen. It allows you to work with database just like you are working with Scala collections. Slick API is asynchronous in nature making it suitable for building reactive applications. Although Slick itself is asynchronous in nature, internally it uses JDBC which is a synchronous API. Slick is a big topic so today we will only cover basics. I will write couple more parts to this blog.

The core idea behind Slick is that as a developer you don’t have to write SQL queries. Instead, library will create SQL for you if you build the query using the constructs provided by the library.

You can read full blog here https://github.com/shekhargulati/52-technologies-in-2016/blob/master/04-slick/README.md