Free online CSV to DB converter

A desktop application may require a database file instead of a spreadsheet-style export, or a local program may need indexed queries and structured storage. Converting the data creates a database that can be opened by the target engine, but the required .db format depends on that application.

What the CSV format is

CSV (comma-separated values) is plain text arranged in records and fields. Rows usually represent records, while commas, semicolons, or tabs separate fields; quoted values can contain separators, quotation marks, or line breaks.

Excel, LibreOffice Calc, accounting systems, contact managers, database exporters, and scripts commonly create CSV files. CSV is useful for exchanging tabular data because many programs can read it, but it does not store table relationships, indexes, constraints, permissions, formulas, queries, or reliable column types.

What a .db file is

.db is a filename extension rather than one universal database format. It often identifies a SQLite database, but Microsoft Access, dBase, Berkeley DB, and proprietary applications also use database files with different internal structures. Confirm the database engine required by the destination program before converting.

A SQLite database stores tables, indexes, constraints, views, and schema metadata in one portable file. SQL queries, transactions, primary keys, and indexes make it more suitable than CSV for repeated searches and application storage. SQLite uses declared column types and type affinity; it cannot infer correct types or relationships that are missing from the source data.

Conversion methods

For a SQLite-compatible .db file, the SQLite command-line program provides a direct import:

1. Back up the CSV and identify its delimiter, encoding, quote character, and header row.
2. Open a terminal in the folder containing the CSV.
3. Run sqlite3 output.db. SQLite creates the file if it does not exist and opens it if it does.
4. Create a table whose columns match the CSV, then import the records.

CREATE TABLE customers (
  id INTEGER PRIMARY KEY,
  name TEXT NOT NULL,
  email TEXT,
  joined_at TEXT
);
.mode csv
.import --skip 1 customers.csv customers
CREATE INDEX customers_email_idx ON customers(email);
.quit

Use --skip 1 only when the first row contains headings. The number and order of imported fields must match the table definition. For a semicolon-delimited file, set .separator ";" before .import; configure the corresponding tab delimiter for tab-separated data. On older SQLite command-line versions that do not support --skip, remove the header row first or import into a staging table and delete the header record.

For a graphical workflow, DB Browser for SQLite can import a CSV through File → Import → Table from CSV file. Select the delimiter, quote character, encoding, and header-row option, review the detected column types, then save the database. The exact menu labels can vary by version.

Python is preferable when the source needs cleaning, validation, type conversion, duplicate handling, or custom null rules:

import csv
import sqlite3

with sqlite3.connect("output.db") as db:
    db.execute("CREATE TABLE customers (id INTEGER, name TEXT, email TEXT)")
    with open("customers.csv", newline="", encoding="utf-8-sig") as file:
        rows = csv.DictReader(file)
        db.executemany(
            "INSERT INTO customers (id, name, email) VALUES (?, ?, ?)",
            ((int(row["id"]), row["name"], row["email"]) for row in rows)
        )

For a no-installation option, use the CSV-to-DB converter on 101convert.com and select the database type supported by the destination program. Do not upload confidential data unless the service’s current privacy terms and handling requirements are acceptable.

If the target is Microsoft Access, dBase, or another non-SQLite database, use that product’s CSV import function or a converter that explicitly supports its format. Renaming a SQLite file to another extension does not convert it.

Quality and compatibility checks

• Confirm the engine: a SQLite .db file will not necessarily open in software expecting Access, dBase, Berkeley DB, or a proprietary database.
• Preserve encoding: UTF-8 is the safest interchange choice. Incorrectly detected ANSI or legacy encodings can corrupt accented characters and non-Latin scripts.
• Define types deliberately: CSV has no native date, Boolean, integer, or decimal type. Store ZIP codes, account numbers, and other identifiers as TEXT when leading zeroes matter.
• Parse CSV correctly: commas inside quoted addresses, embedded newlines, and escaped quotation marks require a CSV-aware importer, not simple string splitting.
• Check values: compare source and destination row counts, inspect null and empty fields, test dates and decimal precision, and run SELECT COUNT(*) FROM customers;.
• Design relationships separately: repeated customer, product, or category data may need normalization into several tables with primary and foreign keys; a file conversion cannot infer that schema reliably.
• Save the database explicitly: commit the transaction, close the database cleanly, and test the resulting file with the same application that will use it.