Project
DuckDB is an open-source, in-process analytical database (OLAP) built for fast SQL on local or embedded data, often used to query Parquet and Iceberg files.
Amazon S3, S3 Tables and S3 Vectors can now be created from the Vercel Marketplace and v0, with no AWS console step for policies or credentials. Functions trade short-lived OIDC tokens with AWS STS, so no static keys sit in the project.
Reality
DuckDB v2.0's CLI agent mode cut the DuckDB output a coding agent reads by 59% in a 132-run test DuckDB published. Total cost and runtime did not improve, the post says, so a team adopting the mode gets clearer output and no smaller invoice.
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RustFS embeds an Apache-2.0 Iceberg REST catalog in its object store and serves it on the S3 port, according to a dev.to walkthrough. Teams can drop a separate metastore, but catalog metadata then shares a failure domain with the data.
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A dev.to walkthrough found DuckDB's operator names in the EXPLAIN output of AWS's aurora_analytics extension, on a Parquet query that executed in 81 ms. That run hit a warm cache on one 500,000-row file, so it tells you which engine ran far more than how fast it will be on lake-scale data.
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Cloudflare made its Data Platform generally available as Basin, three serverless services that ingest, catalog and query Apache Iceberg tables on R2. Outside Iceberg engines read the same tables, so Workers teams can price Basin SQL against a warehouse on identical data.
Perspective Coverage
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AWS has embedded DuckDB in Aurora PostgreSQL from versions 17.11 and 18.6, so one SQL query can join live rows with Iceberg and Parquet tables in S3. Reverse-ETL jobs that exist only for that join can be retired if the database instance has room for the lake scans.
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Apache Iceberg's REST Catalog spec now lets a catalog return per-user row filters and nine column actions for a trusted engine to enforce, Databricks says. Policies that need subqueries or lookup tables do not fit that vocabulary, so the portability covers simple rules running on engines a deployment already trusts.
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Sentinel's builder trained its alert model on fraud versus cleared cases, reaching 0.9465 AUC after three passes that over-called fraud on every case. The finished agent lets an LLM write the explanation and leaves every action to fixed bank rules.
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A one-line change to the open call leaves a real database file in the browser, with a write-ahead log and checkpoints that survive a restart. Getting it to persist depends on which DuckDB-Wasm build you installed.
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A dev.to post argues that Snowflake-managed Iceberg tables let you keep the managed engine while owning the Parquet in your own bucket. The same post says the catalog stays Snowflake's, and that 50,000-inserts-per-second ingest should not move.
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The AllRates dataset on Hugging Face holds 14.6 million rows in each publisher's own direction and label, so the collecting is finished while the inversion, rounding and missing-day rules stay in your code.
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A new Iceberg REST Catalog addition lets the catalog evaluate policy for one principal and return nine column actions plus row filters for a trusted engine to apply, while the spec leaves establishing that trust to the deployment.
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An investing knowledge graph scores mention pairs at 0.96 and 0.12 and calls everything below a high confidence mark a split, on the reasoning that a fabricated edge costs more than a missing one.
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One walkthrough runs both of Sling's modes against a single MySQL table, and the polling mode finishes clean while five cancelled orders stay behind in DuckDB. That gap is a property of SELECT, not of scheduling.
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Hebbian Robotics, a two-person YC Summer 2026 company, announced HFlow on August 19 and shipped it to PyPI the next day, betting that robot dataset checks and provenance are worth sharing between teams rather than rebuilding.
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The engine stays in-process and MIT-licensed, so a vendored copy keeps working after the deal closes. What changes is who decides which storage paths get engineering attention, and the post names six AWS services.
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DuckLabs keeps its Amsterdam desks and the MIT license still holds. The change is who pays for the roadmap, and what that does to a database compiled into your product.
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AWS says the DuckDB projects stay free and open under an independent foundation. The people who write them join AWS by early September, on terms nobody disclosed.
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The MIT-licensed projects stay with the DuckDB Foundation, but the more than 30 people who write them would sit on AWS's payroll. No reporting line has been published.
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MotherDuck's first acquisition buys the runtime that was already executing its agent-written pipelines. The instructive part is what Jordan Tigani says the agents cannot do.
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