What a dump contains
When you export a relational database to a SQL file you get a sequence of ordinary SQL commands written as text. Usually the schema comes first — CREATE TABLE statements that declare each table’s columns, types, keys and constraints — followed by the data as a long run of INSERT statements, one or more rows at a time. Replaying that script against an empty database rebuilds the tables and refills them, which is why SQL dumps are the standard way to back up, migrate or share a dataset. Because it is plain text, a dump can be read, edited, version-controlled and diffed like any other source file, and it does not tie you to a particular binary backup tool.
The format is also self-documenting in a useful way: the CREATE TABLE statements record exactly how the data is structured, so a SQL dump carries its own schema rather than relying on an external description. That makes it a good archival and hand-off format even when the original database is long gone.
The dialect problem
SQL is a standard in name more than in practice, and dumps expose the gaps. MySQL, PostgreSQL and SQLite differ over data types, how identifiers and strings are quoted, auto-increment columns, and the non-standard extensions each adds to its export. A dump produced by one system therefore will not always load cleanly into another without edits — a PostgreSQL dump may use types or syntax MySQL does not recognise, and so on. For straightforward CREATE TABLE and INSERT scripts the differences are usually small and easily adjusted, but for anything using vendor-specific features you should expect to target a particular database rather than assume universal portability.
Strengths
- Plain text — readable, editable, diffable and friendly to version control.
- Carries its own schema in the CREATE TABLE statements.
- The standard, tool-agnostic way to back up, migrate or share data.
- Replaying the script reconstructs both structure and contents.
Limitations
- Dialect differences mean a dump is not always portable between databases.
- Large dumps can be slow to replay row by row.
- Vendor-specific extensions reduce cross-system compatibility.
- Editing a huge generated script by hand is error-prone.
When to use SQL
Use a SQL dump when you need to back up, migrate or hand over a dataset together with its schema, ideally targeting the specific database system that will load it.
SQL FAQ
- How do I import a .sql file into a database?
- Run the script against your database with its command-line client or an admin tool — for example feeding the file to the MySQL or PostgreSQL client, which executes each statement in turn. Make sure the target system matches the dialect the dump was written for, or adjust the syntax first.
- Will a MySQL dump load into PostgreSQL?
- Not always without changes. The two differ on data types, quoting and vendor extensions, so a plain CREATE TABLE and INSERT script often needs minor edits, while one using system-specific features may need more substantial rework.
- How does Morphr produce SQL from my data?
- Morphr generates a CREATE TABLE statement to describe the columns and one INSERT per record, building the script entirely on your device. Nested data from a source like JSON is flattened to fit table columns, so the result is a clean relational view of your records.