Inspired by... but admittedly off-topic... I had recently been wondering how people keep a full auditable history of their data. I've used Hibernate Envers in the past or the now seemingly-defunct Temporal Tables extension for PostgreSQL. What are people using these days? Is DoltLab it, or are there more common solutions?
Can’t say what people are using but keen to hear from others. I am looking into this atm, no implementation yet, and some of the things I am reading about are (I’ll add dolt to this list)
Not what I was looking for, but a nice list. Just want to call out, what I've also seen in the article that a sibling comment pointed to: if you're gonna mention Liquibase, why would you not mention Flyway: https://flywaydb.org/
They wrote a blog about database versioning solutions a little while back, which distinguishes schema vs. data versioning tools. I can't say for sure how comprehensive it is, but presumbly it touches on the more well known solutions.
I can’t figure out if this is a real product or a joke site? The name is confusing.
If it’s a real product it’s cool, I’ve wanted something like this for a while (currently I just use git repos full of JSON files but this would be better I think).
If you want experiment quickly and aren't squeamish about putting your data on the internet, DoltHub is easier to get started with. DoltLab is just a (limited) self-hosted version of DoltHub.
Nice. While I haven't used Dolt, I've definitely enjoyed reading the blog, sepecially the MySQL compatability stuff and some of the other fun ones (like the alcohol dispenser project). Good luck guys!
- it's content addresses / merkle DAG all the way down. The commit's hash is something like meta (author, description, timestamp) + parents hash + root value hash. The root value is composed of the schema, and pointers to table and index maps. Tables and indexes are merkle DAGs of the table data organized in a structure a bit like a B-tree, but with cut points chosen by a rolling value hash in order to probabilistically re-synchronize on incremental changes. Some details: https://www.dolthub.com/blog/2020-04-01-how-dolt-stores-tabl... , https://www.dolthub.com/blog/2020-05-13-dolt-commit-graph-an...
- currently table data is stored row major for full rows of the table and so diffing cannot efficiently ignore individual columns.
- direct conflicts are computed on a row-by-row basis, using the primary key of the row. And then constraints and foreign key references are maintained and validated across merges and edits.