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SQLified is a browser-based tool that converts CSV, TSV, and other delimited data files into clean, import-ready SQL —CREATE TABLE plus batched INSERT statements — for PostgreSQL, MySQL, SQLite, and SQL Server.
Unlike free one-off converters that choke around 100K rows, SQLified is built for production-scale loads: it reliably handles files of 1,000,000+ rows. It does smart type inference (INT/BIGINT, NUMERIC scale, dates, booleans, currency), lets you override any column's type, primary key, and nullability, and emits correctly chunked INSERT batches per dialect (including SQL Server's 1000-row limit and MySQL packet limits) so the output imports cleanly the first time.
Free to use for everyday conversions; Pro unlocks the largest files, batched output tuning, and an ad-free experience. A product of Octet Software.
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SQLified's answer:
Our ability to infer data types, and produce massive insert statements quickly across multiple dialects.
SQLified's answer:
After using many online tools and being disappointed, I realized there was a need for a file that can create clean, type aware sql for bulk inserts. The product saves me tons of time every month dealing with large data sets in the payment industry and has reduced frustrations in dealing with them.
SQLified's answer:
There are numerous competitors, but none that do what SQLified does well: this is type inference, and creating runnable SQL script for extremely large inserts in multiple dialects.
SQLified's answer:
SQLified is designed for the solo developer, or the analytical employee dealing with large data sets, csv, or delimited files every day, and struggling with bulk insert. I want to eliminate that struggle so the real work can be done.
SQLified's answer:
Our tools are simple, effective, and require little processing power. We store no data; all work is "ephemeral" and done on the users machine. We do not track, store, or maintain any datasets whatsoever in regards to whatever is converted on the site. We are also not trying to be something we are not. We do what we do, which is flat file to SQL dialect conversion, and we do it well.
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