SLICK, integrating SQL into Scala

Now it’s official – even if version numbers are still preceded by a “zero” major release: SLICK has been publicly announced by Typesafe:

SLICK stands for Scala Language-Integrated Connection Kit, which is more or less the Scala equivalent for LINQ-to-SQL. Note that I say LINQ-to-SQL, not LINQ in general, as Scala already has sufficient means of querying collections using the Scala language itself.

Here’s a sample of what SLICK code will look like (taken from the SLICK website):

object Coffees extends Table[(String, Int, Double)]("COFFEES") {
  def name = column[String]("COF_NAME", O.PrimaryKey)
  def supID = column[Int]("SUP_ID")
  def price = column[Double]("PRICE")
  def * = name ~ supID ~ price

  ("Colombian",         101, 7.99),
  ("Colombian_Decaf",   101, 8.99),
  ("French_Roast_Decaf", 49, 9.99)

val q = for {
  c <- Coffees if c.supID === 101
  //                       ^ comparing Rep[Int] to Rep[Int]!
} yield (, c.price)


q.foreach { case (n, p) => println(n + ": " + p) }

As you can see, SLICK neatly integrates with Scala’s own syntax. As with LINQ-to-SQL, SLICK’s goal is to

“write your database queries in Scala instead of SQL”

This is quite orthogonal to what jOOQ is aiming for:

“SQL was never meant to be anything other than… SQL!”

As a reminder, see my previous blog post about how jOOQ integrates with Scala, and how you can write almost-SQL queries in Scala using jOOQ against 13 popular databases. It would be interesting to compare the two approaches side-by-side in an independent evaluation, to see the pro’s and con’s of each one, in terms of

  • Developer productivity
  • Maintainability
  • Performance
  • Feature scope
  • etc.

I think it’s time someone made that evaluation. An example can be seen here:

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