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cauchyk

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We Scale PgBouncer in ClickHouse Managed Postgres

clickhouse.com
1 points·by cauchyk·13 hari yang lalu·0 comments

Scaling PgBouncer across every core with SO_REUSEPORT and peering

clickhouse.com
4 points·by cauchyk·14 hari yang lalu·0 comments

Query Insights for Postgres, Powered by ClickHouse

clickhouse.com
1 points·by cauchyk·2 bulan yang lalu·0 comments

Pg_stat_ch: We built low-overhead Postgres metrics exporter to ClickHouse

clickhouse.com
2 points·by cauchyk·5 bulan yang lalu·0 comments

ClickHouse: How we made our internal data warehouse AI-first

clickhouse.com
3 points·by cauchyk·8 bulan yang lalu·0 comments

Show HN: A modern C++20 AI SDK (GPT‑4o, Claude 3.5, tool‑calling)

56 points·by cauchyk·tahun lalu·6 comments

Show HN: AI-SDK-Cpp – Unified C++ SDK for OpenAI, Anthropic, and More

github.com
5 points·by cauchyk·tahun lalu·0 comments

Why Every PeerDB Cloud Tenant Still Gets a Private Postgres

substack.com
1 points·by cauchyk·tahun lalu·0 comments

Why Every PeerDB Cloud Tenant Still Gets a Private Postgres

substack.com
1 points·by cauchyk·tahun lalu·0 comments

Building MySQL Change Data Capture for ClickHouse

clickhouse.com
1 points·by cauchyk·tahun lalu·0 comments

Show HN: Model Context Protocol (MCP) Server for ClickHouse

github.com
1 points·by cauchyk·2 tahun yang lalu·0 comments

Postgres to ClickHouse: Data Modeling Tips

clickhouse.com
2 points·by cauchyk·2 tahun yang lalu·0 comments

Change Data Capture (CDC) Tools should be database specialized not generalized

1 points·by cauchyk·2 tahun yang lalu·1 comments

Reducing BigQuery Costs

blog.peerdb.io
76 points·by cauchyk·2 tahun yang lalu·38 comments

Five tips on Postgres logical decoding

blog.peerdb.io
5 points·by cauchyk·3 tahun yang lalu·0 comments

comments

cauchyk
·2 tahun yang lalu·discuss
We've been using the Ubicloud runner for a while at PeerDB[1]. Great value and specially the ARM runners have been helpful to get our CI costs down. The team is really responsive and added the arm runner support within a few weeks of us requesting it.

[1] https://github.com/PeerDB-io/peerdb
cauchyk
·3 tahun yang lalu·discuss
Author of the blog here: I'm a huge proponent of Rust, but in this project while interfacing with BigQuery and Snowflake go proved to be the right choice. There weren't official drivers for these in Rust and also generally onboarding new devs in Go was easier. I also personally think async in rust has a few more releases to go before I would consider it stable.
cauchyk
·3 tahun yang lalu·discuss
To get higher throughput we would need one goroutine to pull from the replication slot while the other is pushing to the target. The idea is to keep the Postgres connection useful and reading the slot while also pushing to the target asynchronously.
cauchyk
·3 tahun yang lalu·discuss
Not all of our code is in Go. PeerDB has multiple components: the workers, the UI and the query layer. Some of which is in Rust, Go and Typescript.

While it would certainly be possible to package them into individual binaries, I found it significantly easier to define the stack in a docker compose file with the requisite environment setup.
cauchyk
·3 tahun yang lalu·discuss
Author of the blog here, curious what a better alternative would be in this context. The channel has to be passed around for the producer and consumer to interface with each other. Are there better patterns for this?
cauchyk
·3 tahun yang lalu·discuss
At my previous job there were multiple use-cases where we used RabbitMQ in conjunction with Postgres. This would've made life so much easier.

Are there any instructions on installing? It'd be great if the `.so`s are released as part of GH releases.
cauchyk
·3 tahun yang lalu·discuss
Hi there, I’m Kaushik, one of the co-founders of PeerDB. PeerDB doesn’t handle schema changes today.

For CDC, change stream does give us events in case of schema changes, we would have to replay them on the destination. Schema changes on the destination are not supported, the general recommendation is to build new tables / views and let PeerDB manage the destination table.

For streaming the results of a query, as long as the query itself can execute (say a few columns were added or untouched columns were edited) mirror job will continue to execute. In case this is not the case, there will be some manual intervention needed to account for the schema changes.

Thanks for the question, this is a requested feature and on our roadmap.