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
}

Coffees.insertAll(
  ("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.name, c.price)

println(q.selectStatement)

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: http://stackoverflow.com/questions/10537766/closest-equivalent-to-sqlalchemy-for-java-scala

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