MapDB VS Exposed

I decided to start with an overview of what open-source options are currently available. When it comes to the implementation of the on-heap cache mechanism, the options are numerous – there is well known: guava, ehcache, caffeine and many other solutions. However, when I began researching cache mechanisms offering the possibility of storing data outside GC control, I found out that there are very few solutions left. Out of the popular ones, only Terracotta is supported. It seems that this is a very niche solution and we do not have many options to choose from. In terms of less-known projects, I came across Chronicle-Map, MapDB and OHC. I chose the last one because it was created as part of the Cassandra project, which I had some experience with and was curious about how this component worked:

So, it's an object database, like Zope's ZODB on Python?

I like the idea, but I'd like to learn about use cases for it.

Otherwise, in Java, MapDB is about as far as I'd be willing to go: https://github.com/jankotek/mapdb/

Anyway, without further ado, I found MapDB (https://github.com/jankotek/mapdb) which does exactly that. Of course, they also provide their own Java collection implementations as well, so I suspect using it with Vavr would be a poor idea, but it is very cool in its own right anyway. Of course, there is also Apache Derby and HSQLDB, and those great options with a long history as well. I haven't played with these in a while though, so I might give them a try again soon for some personal stuff.

In Java I like

https://mapdb.org/

It is more feature rich than you want but in Python I'd probably just use sqlite3 since it is in the standard library.

I have had good results with mapdb

So is it like Exposed for Kotlin which is a typesafe Kotlin DSL for building sql queries? I’ve been looking for something like this in typescript! https://github.com/JetBrains/Exposed

object TestDatabase { private val mySQLContainer: MySQLContainer = MySQLContainer("mysql:8.0.26").apply { withDatabaseName("test-db") withUsername("test-user") withPassword("test-password") start() // Start the container } init { val config = HikariConfig().apply { jdbcUrl = mySQLContainer.jdbcUrl username = mySQLContainer.username password = mySQLContainer.password driverClassName = "com.mysql.cj.jdbc.Driver" maximumPoolSize = 10 } val dataSource = HikariDataSource(config) // This doesn't connect to the database but provides a descriptor for future use // In the main app, we would do this on system start up // https://github.com/JetBrains/Exposed/wiki/Database-and-DataSource Database.connect(dataSource) // Create the schema transaction { SchemaUtils.create(Users) } } }

Exposed SQL is pretty good.

I am using Kotlins Exposed DSL to access my postgreSQL database. I am running an SQL query which involves doing a one-to-many left join, with the first table having tens of thousands of rows and the second table having millions of rows. The database is stored locally on the machine. I would expect the returned query to be less than one thousand rows.

I understand that `referrersOn` and `referencedOn` can be used, however in the documentations StarWars example, the child table needs to have a column indicating the parent_id row it is joined to. This does not work in my case as my child table can be associated to multiple parent_ids.

I am following this wiki to learn kotlin exposed. It contains an example of 'Referencing' using Star Wars data. I would like to create a scratch and/or console file in IntelliJ which reproduces this simple example. However When I try to run the code I get errors (see below). Is there something I am missing here?

Exposed by JetBrains https://github.com/JetBrains/Exposed

Alternatively there are... hybrid solutions like Kotlin's https://github.com/JetBrains/Exposed or https://jdbi.org/ that don't quite... do all the heavy lifting for querying but allow you to sorta stitch queries together manually.

In our last episode (https://youtu.be/Uza\_dWsNMUs) we worked out how to save stock items in PostgreSQL (https://www.postgresql.org/) using the JetBrains Exposed library (https://github.com/JetBrains/Exposed). This time we refactor our existing file-based storage, extracting an interface that we can implement with files, in-memory, or with Exposed. For the database version, instead of replacing items in a table when they change, we choose to implement an append-only datastore. This keeps all the old versions of every row, using a query to select the latest versions when we want to see the current state. This has the advantage that we can rebuild the state of our system if things go wrong, and may also be faster than amending when we consider transactions. This is part 62 of an exploration of where a Test Driven Development implementation of the Gilded Rose stock control system might take us in Kotlin. You can see the whole series as a playlist https://www.youtube.com/playlist?list=PL1ssMPpyqociJNwykAOB9\_KEZVW7BW7m2 and the code on GitHub https://github.com/dmcg/gilded-rose-tdd If you like this, you’ll probably like my book Java to Kotlin, A Refactoring Guidebook (http://java-to-kotlin.dev). It's about far more than just the syntax differences between the languages - it shows how to upgrade your thinking to a more functional style. I have some free time between producing videos and working for team Gilded Rose. If you like these videos I'd like to work with you - please get in touch - [email protected]

I have used hikari and exposed to do this in the past with postgres, although other dialects are supported.