by Sawyer X
Operation Evergreen began quietly that winter.
Santa had announced it as a workshop-wide initiative to improve the speed and efficiency of analytics across every team (logs, metrics, scheduling, routing, and storage). The elves who maintained the Workshop’s growing systems found themselves gathered around long benches, examining slow queries, performance charts, and the output of tools that strained under seasonal load.
One of the key engines behind Evergreen was Melian, a high-performance caching service designed to answer structured queries faster than any relational database or caching server could hope to. Melian’s protocol was compact and binary; queries were made of tables, indexes, and tight payloads. Round-trip times were measured in single microseconds.
Melian already had clients in Perl, Python, Node.js, PHP, and C. But Evergreen wasn’t only about speed, it was also about making engineering work pleasant. In the workshop, comfort matters, even when you’re racing the calendar.
So one team of elves wondered: Could Raku be the next great way to talk to Melian?
They suspected it could. And they were right.
Enter Raku
These elves were familiar with Raku‘s reputation: expressive, concurrent, type-driven, joyful with binary data, and backed by a runtime that had been quietly optimized for real workloads. But this was the first time they’d attempt to pair Raku with a high-throughput caching server.
To their surprise, Raku behaved as if it had been waiting for precisely this job.
Why Raku Was a Natural Fit for Melian
Melian’s goals were simple: serve rows faster than anything else and handle extremely high request rates while avoiding unnecessary overhead and keeping the client interface small and predictable.
That meant the client language needed to handle structured bytes, concurrency, efficient encoding/decoding, and predictable performance without becoming tedious for the elves writing the code.
Raku checked every box.
Bufs, Blobs, and Native Binary Handling
The elves quickly discovered that Raku treats binary data as a first-class citizen.
For a protocol like Melian’s, you don’t want ceremony. You want to construct frames, inspect bytes, slice, encode, decode, and rebuild messages without tripping over your language.
Raku’s built-in buf8, Blob, and typed native arrays made that simple. These weren’t add-ons or foreign modules; they were part of the core. Conversions between Blobs, Bufs, native arrays, and flat integer lists were natural and efficient.
This meant the elves could remain close to the metal, constructing packets in the exact format Melian required, while still enjoying Raku’s expressive and readable style. Nothing felt clumsy or forced.
It was the first moment the elves realized: this language might actually be built for this kind of work.
Types That Make the Interface Behave
The next advantage became clear when designing the interface.
Raku lets you describe the shape of your data directly in method signatures:
method fetch-by-int(
UInt:D $table-id, UInt:D $index-id, Int:D $key --> Promise
) { ...
If a caller passes the wrong type, Raku catches it immediately. No mysterious errors. No silent failures. The elves loved this because Evergreen required reliability as much as raw speed.
Of course, Raku could have made this even fancier. Its multi-method dispatch system could distinguish between fetch(Int), fetch(Str), fetch(Blob), or even custom types. Many languages struggle with this; Raku does it effortlessly and beautifully.
But for clarity (and in keeping with other Melian client libraries), the elves chose to expose explicit methods such as fetch-by-int-from() and fetch-by-string-from().
The key point remained: Raku let them decide the interface, and it supported both elegant magic and predictable simplicity.
Promises, Auto-Scheduling, and Combinators
Melian encourages parallelism. Most workloads involve fetching many keys at once. That meant concurrency mattered.
The elves knew Raku had Promises, but they didn’t realize how good they were.
Raku’s Promises:
- Auto-schedule onto the thread pool.
- Requires no executor setup.
- Integrate cleanly with typed signatures.
- Compose using
Promise.allof, Promise.anyof, and then chains.
- Behave predictably even with deep asynchronous pipelines.
The elves had spent years managing thread pools manually in other languages. Here, the threading happened automatically. Not only did this simplify Evergreen’s code, but it made Melian’s parallelism feel lightweight.
Even better, Raku offered concurrency tools (like react, whenever, supplies, and channels) that served as powerful constructs, letting elves orchestrate constant streams of cache traffic if the need arose.
They didn’t use these for the basic client, but knowing the tools existed gave the elves confidence: Raku scales with you, not against you.
Parsing Strength: Grammars and Beyond
Melian’s wire protocol is intentionally small, but some elves wondered if future versions might include richer metadata or structured commands.
Raku’s grammars reassured them.
Raku is one of the strongest parsing languages ever built. Grammars are not a library. They are a language feature that provides tokenization, backtracking, parse trees, and consistent error reporting. All are built directly into the syntax.
Even though Melian doesn’t require grammars today, the elves knew that if Evergreen ever needed a more expressive protocol, Raku would handle it without friction.
Rakudo and MoarVM
Finally, the elves examined how this all actually ran.
The client was implemented in Rakudo, powered by MoarVM. MoarVM shines when dealing with:
- native buffers
- concurrent workloads
- object specialization
- byte-level operations
- predictable execution of Promise chains
The elves noted something unusual: Raku’s abstractions didn’t cost them performance. MoarVM carried its weight quietly and efficiently.
Melian was fast, and Raku let the elves keep it fast.
A Walk Through the Raku Client
With these features combined, the Raku Melian client ended up being compact and comfortable:
- binary frames built from buf8
- typed method signatures
- Promise-based fetch operations
- lazy schema bootstrapping
- readable byte decoding
The elves could issue dozens (or hundreds) of concurrent requests, await them, and process results transparently. Where other languages required scaffolding, Raku needed only a few lines.
Evergreen’s goal was speed without sacrificing happiness. Here, Raku delivered both.
A Greener Christmas
By the time Operation Evergreen wrapped up, the Workshop’s analytics systems were faster than ever. Melian handled impossible workloads with ease. And the Raku client provided an expressive, type-safe, concurrent interface that let elves build tools quickly and confidently.
The elves didn’t replace any existing languages. They simply added another one: one that complemented Melian beautifully.
This was the true spirit of Evergreen: enhancing what worked, exploring what could, and giving the workshop more ways to succeed.
Melian stayed fast. Raku made using it pleasant. And somewhere between them, Christmas became just a little greener.
Do It Yourself: Try Melian with Raku
Step 1: Create a SQLite Database
Create a file called workshop.db and load this schema:
CREATE TABLE production (
id INTEGER PRIMARY KEY,
elf_name TEXT NOT NULL,
toys_made INTEGER NOT NULL
);
INSERT INTO production (elf_name, toys_made) VALUES
('Elanor', 42),
('Tarn', 44),
('Pip', 39);
You can inspect it with:
sqlite3 workshop.db 'SELECT * FROM production'
Step 2: Point Your Melian Daemon at the Table
Run Melian in the command line with:
MELIAN_DB_DRIVER=sqlite MELIAN_SQLITE_FILENAME=workshop.db MELIAN_TABLE_TABLES='production#0|60|id#0:int;elf_name#1:string' ./melian-server
This gives us a SQLite DB driver, using the production table, defining two queryable columns (id and elf_name), assuming each will return only one row.
Step 3: Query the Data from Raku
Here is a small example that fetches entries for one elf across multiple hours:
use Melian;
my $melian = Melian.new;
my @names = <Elanor Pip>;
my @promises = @names.map({
$melian.fetch-by-string-from( 'production', 'elf_name', $_);
});
await Promise.allof(@promises);
@promises>>.result.say;
From here, you can extend the example to compute averages, compare elves, or schedule periodic lookups using concurrency constructs.
Letters from the North Pole
Operation Evergreen pushed the Workshop to explore new territory: faster caching, better concurrency, and cleaner interfaces. Melian provided the performance. Raku provided the language that made the client both fast and pleasant to use.
With strong binary types, a real type system, Promises and combinators, a parsing engine ready for any protocol – all built on Rakudo + MoarVM’s efficient execution model.
Raku Advent Calendar 