... Over the past couple of years I ve been building infrastructure for data platforms and AI systems. My background is in analytics engineering, cloud data platforms, PostgreSQL, Snowflake, and AWS, but lately my focus has shifted toward building products rather than consulting. My current project is pg-cdc , an open-source PostgreSQL Change Data Capture platform that continuously publishes changes to modern data lake formats like Parquet and Apache Iceberg. The motivation came from seeing teams spend weeks wiring together ...

... Basedash s AI analyst is now more rigorous about the kinds of questions that trip up most tools. It s more careful with ambiguous metrics, distinguishes named rates from their supporting deltas, notices when a data source is stale versus fresh, and double-checks compound, multi-part answers before responding so you get answers you can trust, with the caveats that matter. We also taught it production-tested SQL gotchas for the databases you actually use Postgres, Supabase, Redshift, Snowflake

... sync to BigQuery 12x less memory 6x less CPU Configured by clicking no SQL, no YAML, no glue code What's live today: - Sources: GitHub, Stripe, Salesforce, Jira, Shopify, HubSpot, Postgres, MySQL - Warehouses: Postgres, BigQuery, ClickHouse, Snowflake Free dedicated worker, no credit card https://apitap.dev/ Pre-launch, so brutal feedback > polite encouragement: 1. Is "managed + lightweight + click-only" a real wedge, or am I solving for yesterday's problem? 2. Which source connector should I prioritize next? 3. What ...

... SaaS have all the possible integrated tools collecting data, but no data analyst to make it work for them. claribi.com is live now! Most analytics advice online is written for one of two audiences. Big data teams with a Snowflake bill and a Looker license. Or solo founders running everything in a Google Sheet. If you sit between those two, running 5 to 100 people with revenue data scattered across Stripe, HubSpot, your product database, and a CSV your ... ... grew Y because of Z, here is what we are doing next" is the headline. OKRs tie strategy to metrics Objectives are aspirational. Key results are measurable, time-bounded, and have an owner. The parts people get wrong: Leading vs

... entire result set to the browser and let it sort itself out. Same deal for Spanner. A lot of Basedash is just "run the SQL the user wrote, show the rows." We support 10+ dialects (Postgres, MySQL, BigQuery, Snowflake, Athena, SQL Server, Spanner, and friends), and every query gets paginated because we can't stream a 12M row result set to a browser. For years the approach was wrap-and-pray. Take whatever the user wrote, stuff ...

... your story, your voice. Excited to be here! Any other writers here who also ended up building something? Comment from Peter Claridge(@peterclaridge): I've recently been wondering whether it's possible to create a browser version of the Snowflake method of story writing but it seems like a daunting task to manage all the components that go into story writing. And Scrivener probably does it better anyway. Are you launching your app on PH? Comment from Susanne Ertl(@susanne ... ... ertl): @peterclaridge  Yes, planning to launch on PH soon . I ve already built it, just figuring out how to present it for the launch. It s quite different from Snowflake

... projects for you to reach the similar position, we have had 1500+ engineers on our platform from people working as quants in Jane Street, Citadel, IMC Trading, Graviton, Optiver to software companies like Google, Amazon, Uber, Databricks, Snowflake, Twilio, Confluent, Rippling. We even have some researchers from Google Deepmind, Anthropic and other frontier AI labs, you can all get to know what you need to do to your profile to reach where they are. Obviously your context matters ...

... integration testing, and pipeline development. Schema-driven: Use your DDL, JSON Schema, or OpenAPI 10+ domain packs: SaaS, e-commerce, fintech, healthcare, IoT ETL modes: full snapshot, incremental, CDC, bronze/silver/gold Export to Parquet, JSON, CSV, SQL, load to Postgres, Snowflake, BigQuery Integrations: dbt seeds, Great Expectations, Airflow DAGs Open source. Python backend. Next.js UI. Local-first. https://github.com/ojasshukla01/... Would love feedback, especially from other data engineers. What would make this more useful for your workflows ...

... community. We're starting out with 2 data agents: - DataChatAgent: Connects to any number of database connections and queries your database - MermaidAgent: Creates a mermaid visualization for an ERD diagram based on your database And 6 databases: - Postgres - Snowflake - Athena - MySQL - Redshift - SQL Server Let us know if you have more questions! Comment from Andreas Martinson(@andreas_martinson): @david_richard35  BigQuery is next in my sights. Very likely to add that before the end of January ...

... take your note-taking to the next level. Experience the Joy of Note-Taking with VaultNote! With VaultNote App, taking notes isn t just easy and fast it s also fun! Imagine writing your thoughts while enjoying animated snowflakes in the winter , or listening to your favorite music as you organize your ideas. Even you can choose color theme (my favorite is the Ice Theme with Winter Snowflakes

... security nightmare. Having worked with companies on deploying agents in production environments, I'm sharing an architecture overview of what's been most useful- hope this helps! Layer 1: Data Sources Your raw data repositories (Salesforce, PostgreSQL, Snowflake, etc.). Traditional ETL/ELT approaches to clean and transform it needs to be done here. Layer 2: Agent Views (The Critical Boundary) Materialized SQL views that are sandboxed from the source acting as controlled windows for LLMs to access your data. You know ...

... wiring up sources, cleaning data, and centralizing it - before an agent can even ask its first question. Pylar now does this out of the box. We re source-agnostic. Whether your data lives across multiple databases and warehouses (Supabase, Snowflake, MySQL, etc.), you can connect one or many instantly, no re-architecture required. If you don't have a warehouse yet, we ve got you covered. Pylar ships with 100+ built-in integrations across marketing tools, CRMs, support platforms, product ...

... Contexto is a daily semantic word-guessing game. For the holidays, we ve added a special Christmas theme to bring seasonal cheer to your word puzzles! Key Features: Festive Christmas theme enjoy cozy visuals and snowflakes Daily semantic word challenges guess the secret word using similarity scoring Only 2 hints per day makes the game competitive and strategic Leaderboard & stats track your streaks and compete globally Fast and mobile-friendly play anywhere, anytime ...

... Product Hunters! We re excited to announce that we ll be launching Jordium.Snowflake.NET very soon a lightweight, high-performance Snowflake-style ID generator designed specifically for .NET developers. If you ve ever struggled with generating unique IDs in distributed systems, this library is for you. It s easy to integrate, configurable, and built for scalability capable of generating millions of unique IDs per second. Stay tuned for the official Product Hunt launch link , and we d love your feedback ...

... Tower over the past few months, with huge progress since 2024. Tower now connects directly to your data, automatically builds semantics, transformations, and dashboards, and generates actionable insights in minutes. New in 2025.10: Tower Pipelines: Combine multiple sources (HubSpot, Snowflake, Airtable, Excel, Databricks, MS SQL, Tally Prime, and more) without a separate ETL tool Tablet Apps: AI-native dashboards for iOS & Android Smarter AI analytics & new connectors Intelligent data transforms Tons of performance and UI/UX improvements Question ...

... Today, we re excited to launch Airbook AI - an AI-native workspace to do all your analytics in one place. Airbook automatically syncs, cleans, and centralizes data from HubSpot, Amplitude, GA4, Zendesk, Stripe, Postgres, Snowflake & more. Our AI is schema-aware - it understands your question and maps it to the fields that exist in your database, auto-builds queries across sources, and lets you edit everything it generates too- so you're always in control. From there, turn results ...

... recently came across some news: Claude for Financial Services officially launched in mid-July. It s designed specifically for the finance industry, integrating data from platforms like PitchBook, Morningstar, Snowflake, S&P Global, and Databricks to support market research, due diligence, and investment decisions. During early testing, Claude Opus 4 hit 83% accuracy on complex Excel tasks. It really makes me question how much room there is left for AI Agent startups ----LLMs are getting better at handling more ...

... starting again and testing, I'm happy to announce that my synthetic data generator for financial card transaction data is now live! It's based on an industry standard spec for base raw data files, requires no input, unlike Snowflake's synthetic data generator procedure, runs fully within the user's environment, so there's no leaks and no data in transit and it's very fast. It can generate approximately 500k rows (40k customers, 1-3 cards per customer ... ... 200k authorized and 200k posted transactions) in under 30 seconds on Snowflake

... office out of a tiny apartment in the East Village, NYC. Since then we ve grown to a team of 30 people in our Soho office serving thousands of customers, from small startups to massive orgs like Shopify, Snowflake, Datadog, and more! So many companies right now are focused on the inner loop of software development: using AI to generate code. However, anyone who has been a software engineer at a larger company knows this is only half ... ... those changes, saving hours of back-and-forth review cycles. What you're seeing is Graphite growing into that vision for an end-to-end pull request toolchain. Graphite users can now: Create stacked PRs with our CLI & VS

... trend in SaaS is app developers bringing their applications to their customers data. Next week, we're teaming up with Snowflake and talking to the Head of Security of Anecdotes (Esther Pinto), CEO of Supergrain (George Xing), and CEO of Rudderstack (Soumyadeb Mitra) about why startups are building their apps on top of customers data platforms. What questions do you have for this panel? What do you want to know about this new deployment model ...