HN user

karakanb

722 karma

co-founder & ceo of Bruin (getbruin.com), building the next generation serverless data platform.

Posts34
Comments139
View on HN
bruin-data.github.io 6d ago

Show HN: Ingestr CDC – open-source CDC replication in Go

karakanb
2pts2
getbruin.com 1mo ago

Migrating from Python to Go with a 12x speedup

karakanb
3pts0
github.com 2mo ago

Show HN: DAC – open-source dashboard as code tool for agents and humans

karakanb
119pts35
getbruin.com 3mo ago

Building an AI Data Analyst Sucks

karakanb
1pts1
getbruin.com 4mo ago

A case for Go as the best language for AI agents

karakanb
203pts293
news.ycombinator.com 7mo ago

Show HN: I built an MCP server to connect AI agents to your DWH

karakanb
1pts1
getbruin.com 9mo ago

The effective LLM multi-tenant security with SQL

karakanb
1pts0
getbruin.com 10mo ago

A story about hunting zombie tasks in a distributed environment

karakanb
22pts3
www.getdbt.com 1y ago

Dbt Labs acquires SDF Labs

karakanb
109pts48
github.com 1y ago

Show HN: I built an open-source data pipeline tool in Go

karakanb
200pts48
burakkarakan.com 1y ago

Visiting San Francisco as a European Resident

karakanb
1pts0
blog.getbruin.com 2y ago

The Pains of Data Ingestion

karakanb
1pts0
github.com 2y ago

Show HN: I built an open-source data copy tool called ingestr

karakanb
156pts48
getbruin.com 2y ago

The Mythical Data Team

karakanb
1pts0
news.ycombinator.com 2y ago

Ask HN: What container registry do you use for your hobby projects?

karakanb
2pts1
saasstarterkit.app 5y ago

Show HN: I built a SaaS starter kit with Docker, Kubernetes, CI/CD and more

karakanb
3pts2
medium.com 5y ago

From 15,000 Database Connections to Under 100

karakanb
4pts1
medium.com 5y ago

An Optimization Exercise in Golang

karakanb
1pts0
saasstarterkit.app 5y ago

Is PHP still relevant in 2021?

karakanb
7pts5
news.ycombinator.com 5y ago

Ask HN: Would you pay for ARM-based dedicated instances?

karakanb
3pts8
burakkarakan.com 5y ago

Remove ads from your life using Raspberry Pi, Docker and Docker Compose

karakanb
5pts2
www.dev 5y ago

Web Stories by Google

karakanb
1pts0
medium.com 6y ago

Lightning Fast Testing for Subscription Payments with Stripe and Laravel

karakanb
1pts0
towardsdatascience.com 6y ago

Python vs. R for Data Science

karakanb
2pts0
levelup.gitconnected.com 6y ago

Jupyter Notebook Best Practices

karakanb
4pts0
levelup.gitconnected.com 6y ago

I bricked my router trying to lock a door

karakanb
2pts0
levelup.gitconnected.com 6y ago

Handling 350k Requests for $3 using Lambda

karakanb
145pts81
medium.com 6y ago

Seniority in Software Engineering

karakanb
37pts35
medium.com 6y ago

What Exactly is Docker?

karakanb
152pts113
medium.com 6y ago

On Seniority in Software Engineering

karakanb
4pts0

İngestr is meant to be a lot more simpler to operate than Debezium and the likes of it, so yes, it makes things a lot easier.

About the staging dump, I haven't tried it but I don't see why it wouldn't work? I'll give it a try.

Yes, we'll create and share a helm chart, although we already publish Docker images so it should be trivial to spin up a chart if you wanted to.

It is not obvious from the post but it seems like the allow list for the scripts supports whitelisting packages instead of a global setting. This should make it easier to maintain org-wise rules to allow scripts only for specific packages.

Is there a linter that could be used for scenarios like this to prevent unsafe default on package manager config?

Hi, this looks interesting, thanks for sharing. I am the builder of ingestr (https://github.com/bruin-data/ingestr), so I am very much in the same space.

I really like that you did this in Go, and I'll definitely dig a bit more into the source code to see how you tackled the CDC stuff, given that there is not many reliable CDC libraries in Go, and there are quite a few gotchas when it comes to doing CDC right. We also hand-rolled ours in ingestr, or I must say clanker-rolled, and we got quite a few things wrong in the first place.

Curious about the postgres-compatible query option: what's the usecase you have in mind there? My perception is that any org that would use Iceberg also has one or a few query engines in place, is this more for debugging stuff?

Quite cool stuff, keep it up!

Zot seems interesting, this is the first time I see it. On a quickl look it seems like Pi, but in Go. I was hoping to embed Pi into some of our internal projects and the typescript stuff was blocking me, I'll definitely give Zot a look.

Thanks! DAC does that kind of validation partially, although doesn't validate the usage of the downstream dashboards. That's a very nice idea though.

In terms of validation it will validate queries, metric definitions, chart definitions and all ahead of time, before render. That way agents tend to validate their work much quicker.

Hi, author here, thanks! I have used TypeScript before across various projects, but I haven't considered building CLI tooling in that before, I guess due to my prejudice against the whole JS ecosystem. I plan to give it another try in the next weeks.

I have been recently looking into extracting a bunch of details from a set of legacy invoice PDFs and had a subpar experience. Gemini was the best among the ones that I tried, but even that missed quite a bit. I'll definitely give this a look.

It seems like such a crowded space and there are many tools doing document extraction, I wonder if there's anything particular pulling more attention into the space?

This seems to undermine the engineering muscle these companies have. Fivetran is well-capable of building a query engine, and with this merger, they also get access to SDF's query engine. They have the engineering capabilities, as well as the capital to attract the talent where needed.

I would not underestimate any of these players in the space.

OpenFlow feels like an attempt at keeping customers within Snowflake boundaries, and while it might work for some, I see no way Snowflake being able to keep up with the data integration needs unless they allow another way of extending their capabilities other than pre-built integrations.

On the other hand, I do agree with you that it is quite a big challenge for Fivetran to try and become Snowflake.

Disclaimer: I am the co-founder of a dbt alternative, Bruin. (https://github.com/bruin-data/bruin)

I think consolidation in the space has been coming for quite some time now and this merger only confirms what us, along with many others, have been saying: the data tooling is in a miserable state and we had to glue together a bunch of different tools that don't work with each other.

At this point, I think it is quite obvious that Fivetran is going for Snowflake/Databricks's market share. They own the ingestion for many companies already, and they will offer a managed data lake product in order to compete with the data giants. By owning the means of bringing the data in (Fivetran) as well as the transformation layer (dbt/sqlmesh) they will aim to get ahead of Snowflakes of the world.

I think it'll be a win for the data community if they maintain and continue investing into the existing tooling, as they are running in quite a few places already, especially dbt core running in a self-managed way. I certainly hope they won't try to squeeze revenue for the sake of it from their combined users.

It's an interesting time to be in the space, and it feels great to be one of the few independent players in the market.

This seems really interesting, thanks for sharing.

I can see myself deploying something like this for some of our internal usecases, however the deployment options around such tooling seem to be rather complicated, especially when it comes to the need for RAG and stuff. Would I need to host something else on top of Upsonic for these sorts of usecases?

while MySQL is very popular, it is very rare to see it in analytical/ML usecases, that's why we haven't added it yet. There's nothing from a technical POV that prevents us from adding, it just hasn't been a priority, I am happy to pull it up if that would help your usecases.

hey, thanks a lot for sharing your thoughts.

I like the comparison page in Hamilton, and in their examples they operate in the asset level, whereas Bruin crosses the asset level into the orchestrator level as well, effectively bridging the gap there. What Bruin does is beyond a single asset that might be a group of functions, it is basically being able to build and run pipelines of that.

In terms of distributed execution, it is in our roadmap to support running distributed workloads as simple as possible, and Postgres as a pluggable queue backend is one of the options as well. Currently, Bruin is meant as a single-node CLI tool that will do the orchestration and the execution within the same machine.