I blogged about this recently - here's a DB schema that can do all of the double entry stuff with about 2 tables. I also have example queries for balance sheets and other useful bits:
I hadn't seen that gem before! My comment on most accounting tools is that they ignore the concept of "normal" account balances, which means they don't really think about "debits" and "credits". This is fine mathematically, of course, but makes it awfully difficult for accountants to understand how the software is supposed to behave!
We're running on mid-sized Postgres right now, but find that clickhouse (or duckdb) are something like 100x faster once we do GROUP BYs on 5M+ rows.
Incidentally, I just came across Journalize. But I'm struggling to understand what it's for. It might be helpful to say - either here, or on your homepage - who or what it is competing with. I'm probably not the exact target audience, but it seems to do more or less what Xero does for us (but I don't want to rule out that I just don't understand the homepage).
If your business generates a lot of transactions, to the point that you have a full time accounting or engineering staff whose job it is to wrangle 200MB excel files or complicated sql queries, then Journalize is for you.
We’re basically BI tailor made to create outputs that are relevant to accountants (we know what “depreciation” is supposed to look like) and let them take a monthly ledger entry and drill down to a specific user’s impact on the GL and tie it to the line of source data.
In this way, we’re doing the data engineering work, helping accounting teams have BI type tools to set up accounting rules, and giving transparency to “why” an aggregate number is correct.
https://blog.journalize.io/posts/an-elegant-db-schema-for-do...
I hadn't seen that gem before! My comment on most accounting tools is that they ignore the concept of "normal" account balances, which means they don't really think about "debits" and "credits". This is fine mathematically, of course, but makes it awfully difficult for accountants to understand how the software is supposed to behave!
We're running on mid-sized Postgres right now, but find that clickhouse (or duckdb) are something like 100x faster once we do GROUP BYs on 5M+ rows.