Alternatives
Products that do what BQMetrics does
Drag and Drop for BigQuery - No SQL needed
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PgQueuer is a minimalist, high-performance job queue library for Python, leveraging the robustness of PostgreSQL. Designed for simplicity and efficiency, PgQueuer uses PostgreSQL's LISTEN/NOTIFY to manage job queues effortlessly.
2024 · github.com
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Hi HN, I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning. We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem. To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic…
Jan 2026 · playground.shaped.ai
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I played around with GPT-3 to build this demo. Select a public BigQuery dataset and describe your query in natural English, then edit the generated SQL as needed and execute it. https://app.tabbydata.com/sql-assistant-demo
2021
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Hi all, we recently open sourced the first version of Hashquery, a Python library which lets you model analytics, DRY up common logic, and execute it against a database or warehouse. We were originally rendering SQL directly for all our queries, but that spiraled out of control with more complex analysis; the SQL needed to be changed sporadically for each new database dialect (BigQuery, Redshift, Aethena, Postgres, etc etc) and the SQL fragments were very challenging to reuse (and so fragments were copy-pasted all over). ~~~ Advantages we think it has over writing SQL by hand: - Queries are…
2024 · hashquery.dev
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I hit a wall recently where we needed to design a data store that can both (1) ingest schema-less updates at scale and (2) allow for large analytical queries. GCP native doesn't have something that does both of these out-of-the-box, so we kinda hacked our own solution by replicating updates from Bigtable into a Type 2 SCD table in BigQuery. i couldn't find many resources online on this sort of trick when I was building it out, so I wrote up this blog with the details. Hope it's helpful and curious if anyone has used or built something similar. Will stick around for comments, happy to answer…
2025 · statsig.com
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I've always been curious about how SQL engines actually work. So I built a minimum viable SQL engine in Go. - Supports CSV files as tables - Supports SELECT, FROM, WHERE, LIMIT It's very simple: 1. Parses query string 2. Converts it into an AST representation 3. Executes the query against the CSV 4. Returns the results
2024 · github.com
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2019 · mprove.io
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I created a web page to compare different analytical databases (both self-managed and services, open-source and proprietary) on a realistic dataset. It contains 20+ databases, each with installation and data loading scripts. And they can be compared to each other on a set of 43 queries, by data load time or by storage size. There are switches to select different types of databases for comparison - for example, only MySQL compatible or PostgreSQL compatible. If you play with the switches, many interesting details will be uncovered. Full description:…
2022 · benchmark.clickhouse.com
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