Glad to see @lbugdb's performance improvements, and especially happy to see our recent work being adopted.
@lbugdb is adapting ideas from our recent SIGMOD 2026 paper to improve vectorized execution over factorized intermediates.
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As part of the Gemma 4 release, we're launching Agent Skills: an Android app experience where you can import different skills and have Gemma 4 E2B reason and use the skills!
Running entirely in the phone, available in the Google PlayStore. Try it now!
Happy to share that our recent work at @DAIS_PolyMTL, “SQLMorph: Query Mutation and Fine-Grained Metrics for Text-to-SQL Evaluation” has been accepted at @ICDEconf 2026, one of the top venues in data engineering. 🧵👇🏻
@priyaaa63@duckdb The project is still a work in progress, but all supported functions are fully operational and tested. We are actively addressing any bugs across multiple platforms and look forward to receiving your feedback 😁.
🚀 We just released Flock v0.7.0, a @duckdb community extension that brings AI operators via LLMs, and RAG directly into SQL.
🧵 Here's what's new 👇
🤖 Anthropic (𝗖𝗹𝗮𝘂𝗱𝗲) 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿 𝗦𝘂𝗽𝗽𝗼𝗿𝘁
Flock now supports four LLM providers: OpenAI, Azure, Ollama, and Anthropic. Define a model once with CREATE MODEL, then swap providers or the model later (admin-side) without changing the SQL queries that use it.
🌐 𝗪𝗔𝗦𝗠 (𝗪𝗲𝗯𝗔𝘀𝘀𝗲𝗺𝗯𝗹𝘆) 𝗦𝘂𝗽𝗽𝗼𝗿𝘁
Flock now compiles and runs inside DuckDB-WASM.
📊 𝗟𝗟𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴
End-to-end observability for your pipelines: token usage, latency, and call counts for all LLM invocations within a query.
🎤 Introduced 𝗔𝘂𝗱𝗶𝗼 𝗧𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽t𝗶𝗼𝗻
Expanded multimodal support with audio transcription (and continued support for images).
If you want semantic and analytical processing in one place, Flock lets you do it all in SQL.
⭐ GitHub: https://t.co/R3surljdOJ
📖 Docs: https://t.co/oqTyAGM3Sf
📝 Paper: https://t.co/eu2g2Thaq4
We'd love your feedback and contributions!
#DuckDB #LLM #SQL #OpenSource #ArtificialIntelligence #RAG #DataEngineering #Anthropic #Claude #WASM #MachineLearning
How to bring AI directly into your SQL workflows? Explore open-source extensions that embed large language model (LLM) capabilities for RAG and semantic analysis. This approach lets data engineers and developers leverage AI in-database, simplifying advanced analytics within familiar SQL.
https://t.co/bsOFHzwMTh
Most data engineers are still wrestling with separate tools for AI and SQL. You're bleeding time and performance. The old way is dead. Here's why: https://t.co/uLn8ChaTZ8
Your 'modern' data stack is obsolete if it can't natively handle AI. Python notebooks are a temporary fix. True data engineering integrates AI directly into SQL. The future demands it.
SQL can feel like a chef trying to whip up a Michelin-star meal with only a spatula and a dream.
But with the right tools, even complex data transformations become a culinary masterpiece.
Don't let your data be a bland dish; spice it up with smart SQL!
If you want semantic and analytical processing in one place, Flock lets you do it all in SQL.
⭐ GitHub: https://t.co/SD6kxW4vDm
📖 Docs: https://t.co/CSe0UwZwOQ
We'd love your feedback and contributions!