fast-sqlite3-inserts VS QuestDB

I am experimenting with SQLite, where I try inserting 1B rows in under a minute. The current best is inserting 100M rows at 23s. I cut many corners to get performance, but the tweaks might suit your workload.

I have explained my rationale and approach here - https://avi.im/blag/2021/fast-sqlite-inserts/

the repo link - https://github.com/avinassh/fast-sqlite3-inserts

I am working on a project [0] to generate 1 billion rows in SQLite under a minute and inserted 100M rows inserts in 33 seconds. First, I generate the rows and insert them in an in-memory database, then flush them to the disk at the end. To flush it to disk it takes only 2 seconds, so 99% of the time is being spent generating and adding rows to the in-memory B Tree.

For Python optimisation, have you tried PyPy? I ran my same code (zero changes) using PyPy, and I got 3.5x better speed.

I published my findings here [1].

[0] - https://github.com/avinassh/fast-sqlite3-inserts

[1] - https://avi.im/blag/2021/fast-sqlite-inserts/

I have a side project where I tried to insert one billion rows in SQLite. I was able to insert 100 million rows using Python under 210 seconds. The same thing with PyPy took 120 seconds. I am wondering what kind of speed boost I would get with Cython

Measure, measure, measure! There is a PR which made really minor changes, but it got 2x speed boost with CPython version

[somewhat related] Recently, I was benchmarking SQLite inserts and I managed to insert 3.3M records per second (100M in 33 ish seconds) on my local machine - https://github.com/avinassh/fast-sqlite3-inserts Ofcourse the comparison is not apples to apples, but sharing here if anyone finds it interesting

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Looks like full keys are always compared if hash codes test equal, which is what I'd expect. For example: https://github.com/questdb/questdb/blob/master/core/src/main...

But of course, I want to run a QuestDB instance on my node, which uses two additional TCP ports for Influx Line Protocol (ILP) and Pgwire communication with the database. So how can I expose these extra ports on my node and route traffic to the QuestDB container running inside of k3s?

In this post, I will detail a way in which I recently used annotations while writing an operator for my company's product, QuestDB. Hopefully this will give you an idea of how you can incorporate annotations into your own operators to harness their full potential.

QuestDB is an open source, high performance time series database. With its massive ingestion throughput speeds and cost effective operation, QuestDB reduces infrastructure costs and helps you overcome tricky ingestion bottlenecks. Thanks for reading!