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Open Source

8 posts

pankhllm: The LLM Gateway That Learns to Skip the LLM, Without Replacing the Stack You Already Run
Data Engineering10 min read

pankhllm: The LLM Gateway That Learns to Skip the LLM, Without Replacing the Stack You Already Run

Most of an agent's LLM calls are not writing anything. They are decisions: which tool, which skill, which parameters, made thousands of times a day by a model paid in seconds and tokens. pankhllm sits where your app already calls an LLM, learns those decisions from its own traffic, and starts making them in 0.2 ms on a CPU with a 262 KB model. What it is not sure about still goes to your LLM. On the same 14 questions: a 12B planner 1,743 ms, Laya 49 ms, pankhllm's own model 4 ms, all 14 correct. Here is what it is, what it is not, and where it stops.

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Apache Arrow Compute on the Apple Silicon GPU: The First Arrow Project I Created That Does It, With 173 Operations Measured Against Polars, pyarrow and pandas
Data Engineering11 min read

Apache Arrow Compute on the Apple Silicon GPU: The First Arrow Project I Created That Does It, With 173 Operations Measured Against Polars, pyarrow and pandas

I built ArrowMetal, the first Apache Arrow project I could find that runs compute on the Apple silicon GPU. Apple silicon has one memory for CPU and GPU, and an Arrow buffer in shared Metal memory is already a GPU buffer; no Arrow project used that. ArrowMetal does: 307 of Arrow's 307 compute functions, seven languages, take at 24.2x pyarrow on an M4 Max, and 339 benchmark rows against the fastest CPU idiom of Polars, pyarrow, pandas and numpy, including the 77 where the CPU is still ahead.

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“PostgreSQL-compatible” Is Not PostgreSQL: What Arrow's Native ADBC Driver Does on 14 Wire-Compatible Databases
Data Engineering12 min read

“PostgreSQL-compatible” Is Not PostgreSQL: What Arrow's Native ADBC Driver Does on 14 Wire-Compatible Databases

I ran the native PostgreSQL and MySQL ADBC drivers against 28 databases that speak their protocols. Half stopped. Then I found a bug in my own driver.

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Apache Arrow ADBC Just Listed My ODBC Bridge on Its Official Integrations Page — Seven Days After v0.1.0
Data Engineering6 min read

Apache Arrow ADBC Just Listed My ODBC Bridge on Its Official Integrations Page — Seven Days After v0.1.0

The Apache Arrow ADBC documentation now lists adbcBridge on its Tools & Integrations page — seven days after I released v0.1.0. I filed the listing request on August 29; on August 31 a project member invited a PR, and it was merged six hours after the invitation. What the entry says, how the week that earned it went, and what it changes for anyone with an ODBC-only database.

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Your ODBC Driver Says SQL_SUCCESS and Lies: 24 Bugs Found in 13 Database Projects (adbcBridge Part 2)
Data Engineering15 min read

Your ODBC Driver Says SQL_SUCCESS and Lies: 24 Bugs Found in 13 Database Projects (adbcBridge Part 2)

Part 2 of the adbcBridge story. Running one workload through 46 databases on three operating systems turned up 24 defects that belong to other projects — twelve of them return wrong or lost data under SQL_SUCCESS. Every one is filed upstream with a reproduction that needs no adbcBridge in the stack. Here is the ledger, what the bugs have in common, and what happened when the maintainers read them: within the first week, two fixes landed upstream and four more fix PRs went up.

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I Built an Apache Arrow ADBC Driver for Every ODBC Database: 46 Databases, 5 Languages, Every Number Measured
Data Engineering21 min read

I Built an Apache Arrow ADBC Driver for Every ODBC Database: 46 Databases, 5 Languages, Every Number Measured

Native Apache Arrow ADBC drivers exist for a handful of databases. The other few hundred ship an ODBC driver and nothing else. adbcBridge is one plain-C11 shared library that turns every ODBC driver on your machine into an Arrow-native ADBC driver — columnar record batches out, bulk ingest in — from Python, Rust, Go, Java and C#. Today it is public: 46 databases verified on Linux, 41 on macOS, 45 on Windows, five languages measured against all of them, and every figure named with the laptop and the load it was taken under.

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When an AI-Generated Answer Actually Works, Who Is the Rule Protecting? A Fair Look at Both Sides — and a Rule Both Could Sign
Opinion10 min read

When an AI-Generated Answer Actually Works, Who Is the Rule Protecting? A Fair Look at Both Sides — and a Rule Both Could Sign

A programming community I take part in watches for AI-generated answers. The moderators have real reasons; so do the people the rule lands on. Here are both cases argued fairly, the three things both sides actually want, and a tiered guideline — verification, disclosure, capacity — that is stricter than a blanket ban, not looser.

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The First SQL Engine for Apple Silicon GPUs Is Now a DuckDB Community Extension
Data Engineering8 min read

The First SQL Engine for Apple Silicon GPUs Is Now a DuckDB Community Extension

In May 2026 I shipped gpudb v0.1 — the first SQL execution engine targeting Apple Silicon GPUs, built as a DuckDB extension with a CUDA backend on Linux. Three releases later, the project crossed two lines at once. v0.3.0's streaming-aggregate rewrite reached parity with native DuckDB on end-to-end TPC-H queries — the worst cell improved roughly 100×, from 11.05 s to 0.109 s. And gpudb became an official DuckDB Community Extension: INSTALL gpudb FROM community now works in any DuckDB ≥ 1.5.5, signed, no flags. This is the full arc — what v0.1 proved, what v0.2 honestly lost, what v0.3 fixed, and why the next GPU frontier is joins.

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