Your first lake

A lake is a folder: on your disk, or a prefix in an S3, R2, GCS or Azure bucket. Pondra keeps your tables there as Parquet files, plus a log of the newest rows. There is no database server to install: one pondra process on the lake answers SQL, Python and JavaScript.

Start a node

pondra serve lake --addr 127.0.0.1:8080

Or let your code start one for you, in the background, and stop it when you’re done:

Python
JavaScript

import pondra
db = pondra.local("lake")   # starts a node on ./lake

import { local } from "pondra";
const db = await local("lake");

The examples below talk to a node at localhost:8080. Open http://localhost:8080 in a browser and you get the console: the lake’s tables, and cells for SQL and Python.

Make a table and write rows

CREATE TABLE orders (id BIGINT, item VARCHAR, qty INT, amount DOUBLE);
INSERT INTO orders VALUES (1, 'tea', 2, 7.0), (2, 'cake', 1, 4.5), (3, 'tea', 1, 3.5);

import pondra
db = pondra.connect("http://localhost:8080")
db.sql("CREATE TABLE IF NOT EXISTS orders (id BIGINT, item VARCHAR, qty INT, amount DOUBLE)")
db.append("orders", [{"id": 4, "item": "coffee", "qty": 1, "amount": 3.0}])

import { connect } from "pondra";
const db = connect("http://localhost:8080");
await db.sql("CREATE TABLE IF NOT EXISTS orders (id BIGINT, item VARCHAR, qty INT, amount DOUBLE)");
await db.append("orders", [{ id: 5, item: "juice", qty: 2, amount: 5.0 }]);

Query it

SELECT item, sum(qty) AS items, sum(amount) AS total FROM orders GROUP BY item ORDER BY total DESC;

print(db.sql("SELECT item, sum(qty) AS items FROM orders GROUP BY item ORDER BY item").rows())

import { connect } from "pondra";
const db = connect("http://localhost:8080");
console.log(await db.sql("SELECT count(*) AS n FROM orders"));