Alternatives
Products that do what DecisionBox for Microsoft SQL Server does
Connect DecisionBox to your MSSQL to validate findings
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Connect DecisionBox to your Databricks to validate findings
May 2026 · decisionbox.io
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Agent that writes SQL for you to validate database insights
Apr 2026 · decisionbox.io
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Autonomous AI discovery on Amazon Redshift.
May 2026 · decisionbox.io
- 4SS
2018 · selectstarsql.com
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2017 · github.com
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- 11DT
I built DDL to Data after repeatedly pushing back on "just use production data and mask it" requests. Teams needed populated databases for testing, but pulling prod meant security reviews, PII scrubbing, and DevOps tickets. Hand-written seed scripts were the alternative slow, fragile, and out of sync the moment schemas changed. Paste your CREATE TABLE statements, get realistic test data back. It parses your schema, preserves foreign key relationships, and generates data that looks real, emails look like emails, timestamps are reasonable, uniqueness constraints are honored. No setup, no…
Jan 2026
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- 13DU
I built Duck-UI, a web-based SQL editor that runs DuckDB entirely in your browser via WebAssembly. No backend required. The Problem: Every time I needed to query csv, parquet, or even to play with SQL, I had to either: (a) spin up a Jupyter notebook (b) use the CLI (c) upload to a hosted service. Friction at every step (TOO MUCH to load a csv or even to test some sql (study)... The Solution: DuckDB's WASM runtime lets us run SQL analysis client-side. Load CSV/JSON/Parquet files from disk or URL, write SQL, get results instantly. Data stays on your machine. What It Does: SQL editor…
Oct 2025 · demo.duckui.com
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- 15DS
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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Hey there! I’ve been working on DB Pilot for the last couple of months, and I recently added an AI assistant powered by GPT 3.5 to help you write SQL queries tailored to your DB schema. Simply ask what data you are looking for - GPT will figure out which tables to use, how to join them, and then write a query for you. The AI assistant knows which tables and columns exist in your database, meaning it can write queries specific to your schema. Besides that, it doesn't have access to any actual data from your database though, meaning your data doesn't get exposed to OpenAI.
2023 · dbpilot.io
- 20GA
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
- 21NL
Hi HN- Today, we are releasing the hosted API for our natural language to SQL engine, which allows you to: (1) Explain Your Data: Feed in dictionaries, dbt, schemas, Confluence docs - we'll understand the business context to your data. (2) Train Your AI: Fine-tune an LLM (including GPT-4) specifically for your data, increasing accuracy and lowering latency (3) Trust the Answer: See confidence scores with each AI-generated query, stay in control. (4) Conduct complex SQL queries Problem background - Developers struggle to build NL-to-SQL into products because LLMs do not work out-of-the-box;…
2024 · dataherald.com
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- 23SD
Jul 2026 · github.com
- 24PA
2021 · github.com
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