litefs VS prisma-engines

Firstly, LiteJob's reliance on SQLite inherently restricts its horizontal scaling capabilities. Unlike other databases, SQLite is designed for single-machine use, making it challenging to distribute workload across multiple servers. This can certainly be done using novel technologies like LiteFS, but it is far from intuitive.

Im curious to know if others have tried out Turso or LiteFS or any of the newer edge db providers that are popping up in 'real world' applications and what your experiences have been?

Author here. I think we could have set better expectations with our Postgres docs. It wasn't meant to be a managed service but rather some tooling to help streamline setting up a database and replicas. I'm sorry about the troubles you've had and that it's come off as us being disingenuous. We blog about things that we're working on and find interesting. It's not meant say that we've figured everything out but rather this is what we've tried.

As for this post, it's not managed SQLite but rather an open source project called LiteFS [1]. You can run it anywhere that runs Linux. We use it in few places in our infrastructure and found that sharing the underlying database for internal tooling was really helpful for that use case.

[1]: https://github.com/superfly/litefs

#. SQLite WAL mode

From https://www.sqlite.org/isolation.html https://news.ycombinator.com/item?id=32247085 :

> [sqlite] WAL mode permits simultaneous readers and writers. It can do this because changes do not overwrite the original database file, but rather go into the separate write-ahead log file. That means that readers can continue to read the old, original, unaltered content from the original database file at the same time that the writer is appending to the write-ahead log

#. superfly/litefs: aFUSE-based file system for replicating SQLite https://github.com/superfly/litefs

#. sqldiff: https://www.sqlite.org/sqldiff.html https://news.ycombinator.com/item?id=31265005

#. dolthub/dolt: https://github.com/dolthub/dolt

> Dolt can be set up as a replica of your existing MySQL or MariaDB database using standard MySQL binlog replication. Every write becomes a Dolt commit. This is a great way to get the version control benefits of Dolt and keep an existing MySQL or MariaDB database.

#. pganalyze/libpg_query: https://github.com/pganalyze/libpg_query :

> C library for accessing the PostgreSQL parser outside of the server environment

#. Ibis + Substrait [ + DuckDB ]

> ibis strives to provide a consistent interface for interacting with a multitude of different analytical execution engines, most of which (but not all) speak some dialect of SQL.

> Today, Ibis accomplishes this with a lot of help from `sqlalchemy` and `sqlglot` to handle differences in dialect, or we interact directly with available Python bindings (for instance with the pandas, datafusion, and polars backends).

> [...] `Substrait` is a new cross-language serialization format for communicating (among other things) query plans. It's still in its early days, but there is already nascent support for Substrait in Apache Arrow, DuckDB, and Velox.

#. benbjohnson/postlite: https://github.com/benbjohnson/postlite

> postlite is a network proxy to allow access to remote SQLite databases over the Postgres wire protocol. This allows GUI tools to be used on remote SQLite databases which can make administration easier.

> The proxy works by translating Postgres frontend wire messages into SQLite transactions and converting results back into Postgres response wire messages. Many Postgres clients also inspect the pg_catalog to determine system information so Postlite mirrors this catalog by using an attached in-memory database with virtual tables. The proxy also performs minor rewriting on these system queries to convert them to usable SQLite syntax.

> Note: This software is in alpha. Please report bugs. Postlite doesn't alter your database unless you issue INSERT, UPDATE, DELETE commands so it's probably safe. If anything, the Postlite process may die but it shouldn't affect your database.

#. > "Hosting SQLite Databases on GitHub Pages" (2021) re: sql.js-httpvfs, DuckDB https://news.ycombinator.com/item?id=28021766

#. awesome-db-tools https://github.com/mgramin/awesome-db-tools

LiteFS works sorta like that. It provides read replicas on all your application servers so you can use it just like vanilla SQLite for queries.

Write transactions have to occur on the primary node but that's mostly because of latency. SQLite operates in serializable isolation so it only allows one transaction at a time. If you wanted to have all nodes write then you'd need to acquire a lock on one node and then update it and then release the lock. We actually allow this on LiteFS using something called "write forwarding" but it's pretty slow so I wouldn't suggest it for regular use.

We're adding an optional a query API over HTTP [1] soon as well. It's inspired by Turso's approach. That'll let you issue one or more queries in a batch over HTTP and they'll be run in a single transaction.

[1]: https://github.com/superfly/litefs/issues/326

Basically, LiteFS: https://github.com/superfly/litefs

And then some load balancer cleverness that reroutes writes to a specific VM: https://fly.io/blog/globally-distributed-postgres/

But my guess is they'll have an alternate implementation or something like LiteFS in Deno Deploy that will make this substantially more interesting when running in the Cloud.

This is a very strange comment section. And this article is insanely poorly written.

> Last week, we completed a migration that switched our underlying database from MongoDB to Postgres.

Okay cool, but why? MongoDB is a very capable and fast database.

> It was a shock finding out that Prisma needs almost a “db” engine layer of its own. Read more about it here: https://www.prisma.io/docs/concepts/components/prisma-engine...

If you did any research on Prisma rather than diving in head-first, you'd realize this is a core part of why Prisma exists.

> we discovered that at a low level, Prisma was fetching data from both tables and then combining the result in its “Rust” engine. This was a path for an absolute trash performance.

Can you confirm this is actually the case? Can you show some benchmarks re: this claim? Or are you just assuming this is the case?

If you wish to auto-generate migrations, there are declarative schema change tools available for most relational databases. I'm the creator of Skeema [1] which provides them for MySQL, but there are options for other DBs too [2][3][4].

Prisma's migration system actually partially copied Skeema's design, while giving credit in a rather odd fashion which really rubbed me the wrong way: "The workflow of working with temporary databases and introspecting it to determine differences between schemas seems to be pretty common, this is for example what skeema does." [5]

While I doubt I was the first person to ever use that technique, I absolutely didn't copy it from anywhere, and it was never "pretty common". I'm not aware of any other older schema change systems that work this way.

[1] https://www.skeema.io

[2] https://github.com/djrobstep/migra

[3] https://github.com/k0kubun/sqldef

[4] https://david.rothlis.net/declarative-schema-migration-for-s...

[5] https://github.com/prisma/prisma-engines/blob/6be410e/migrat...

If you're serious about your review then you shouldn't ignore the fact that Prisma has a big blob of Rust code at its core, where other ORMs use standard database adapters from NPM. As someone who has maintained database adapters for other languages, let me tell you that the maintenance burden of that is quite significant. Especially if they ever want to support more advanced database features. If the company behind Prisma ever runs out of money, the project is probably toast.

prisma generate generates the code for the Prisma client. The code generated for the client is all JavaScript which calls into the “Prisma Engine” Rust native Node module to perform database operations. As others here have said, the Prisma Engine is pre-compiled by rustc via CI and gets dowloaded to your machine as a pre-built binary by npm, so there’s no need for you to build it yourself by running the Rust compiler locally.

Note: you may notice that it downloads some binaries when you first invoke this command. This is normal it fetches the node prisma cli and engines used by prisma. 😁

We solved this with flat vectors and just sharing index values in cheap walker objects. It is much nicer to work with compared to arc/weak pointers.

Code here: https://github.com/prisma/prisma-engines/tree/main/libs%2Fda...

Because Prisma Python currently interfaces with the Rust engine over HTTP (I am looking into changing this) and the Rust engines can be found here:

https://github.com/prisma/prisma-engines

Thanks! I know of a couple Postgres tools that work in a declarative fashion: migra [1] and sqldef [2].

Migra is Postgres-specific. Its model is similar to Skeema's, in that the desired-state CREATEs are run in a temporary location and then introspected, to build an in-memory understanding of the desired state which can be diff'ed against the current actual state. (This approach was also borrowed by Prisma Migrate [3]). In this manner, the tool doesn't need a SQL parser, instead relying on the real DBMS to guarantee the CREATE is interpreted correctly with your exact DBMS version/flavor/settings.

In contrast, sqldef supports multiple databases, including Postgres and MySQL (among others). Unlike other tools, it uses a SQL parser-based approach to build its in-memory understanding of the desired state. As a DB professional, personally this approach scares me a bit, given the amount of nonstandard stuff in each DBMS's SQL dialect. But I'm inherently biased on this topic. And I will note sqldef's author is a core Ruby committer and JIT author, and is extremely skilled at parsers.

[1] https://databaseci.com/docs/migra

[2] https://github.com/k0kubun/sqldef

[3] https://github.com/prisma/prisma-engines/blob/main/migration...

Prisma 2 is a program, written in Rust that exposes a GraphQL API on top of your database of choice. Here's a link to the "engine": https://github.com/prisma/prisma-engines