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you can now get data from auth'd APIs with DuckDB 🤯 ya know, to get your stripe data or whatever (it's not documented yet)

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archie 🦋

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69,200 views • 2 years ago •via X (Twitter)

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What Postgres can’t do alone, it can tackle with DuckDB. The pg_duckdb extension shows how two databases can work hand in hand by querying analytical data with DuckDB and joining it with transactional data in Postgres. The extension embeds DuckDB directly into Postgres. DuckDB literally runs inside a Postgres process. How it works (see diagram): 1. An app sends a query to Postgres joining portfolio data (Postgres) with historical market data (lakehouse) 2. pg_duckdb detects lakehouse access and delegates execution to DuckDB 3. DuckDB pulls required market data from the lakehouse, queries Postgres tables, and performs the join 4. Postgres returns the final result to the app
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What Postgres can’t do alone, it can tackle with DuckDB. The pg_duckdb extension shows how two databases can work hand in hand by querying analytical data with DuckDB and joining it with transactional data in Postgres. The extension embeds DuckDB directly into Postgres. DuckDB literally runs inside a Postgres process. How it works (see diagram): 1. An app sends a query to Postgres joining portfolio data (Postgres) with historical market data (lakehouse) 2. pg_duckdb detects lakehouse access and delegates execution to DuckDB 3. DuckDB pulls required market data from the lakehouse, queries Postgres tables, and performs the join 4. Postgres returns the final result to the app

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OpenAI's Deep Research is getting a run for its money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!
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You can now earn Replit credits when you monetize your apps with Stripe Build. Earn. Get rewarded
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Did you know that SSDs use quantum tunnelling to store data? Or that we have to completely rewrite RAM every 30ms to prevent data from just dissipating? If you did, then you can probably skip this chapter on how computers store data:
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