SQLite
SQL Server

SQLite to SQL Server Converter

Move data between SQLite files and SQL Server in either direction. Schema conversion, type mapping, and optional two-way sync.

SQLite to SQL Server conversion moves a single embedded .db file into a multi-user SQL Server database.

The hard part is not copying rows; it is reconciling SQLite's flexible single-file conventions with SQL Server's strict relational and typed model.


What DBConvert does on this path: handles the file-to-server move as a repeatable desktop workflow:

  • Opens the SQLite database file and lets you review object selection and type mapping.
  • Creates SQL Server-compatible tables and transfers rows from the SQLite source.
  • Writes to SQL Server, SQL Server Express, Azure SQL Database, or Amazon RDS for SQL Server.

What it does not do: application code written around SQLite locking, pragmas, local-file paths, or SQLite-specific SQL still needs review before the application points at SQL Server.

Which tool: DBConvert or DBSync?

DBConvert for SQLite → SQL Server

One-time conversion. Use it when SQL Server is becoming the production database and you need schema, table data, indexes, and type mapping moved from a SQLite file.

DBSync for SQLite ↔ SQL Server

Repeat synchronization. Use it when the SQLite file and SQL Server database must keep exchanging changes during a staged rollout or desktop-to-server workflow.

Need more context? Compare DBConvert and DBSync side by side →

How DBConvert handles the SQLite → SQL Server differences

SQLite is permissive; SQL Server is stricter about schema and server behavior. DBConvert maps most of those differences in the wizard with sensible defaults that you can review or override per table; SQLite triggers and CHECK constraints are the items that still need a human review.

  • Dynamic typing. Inspects actual column values during read and proposes a strict SQL Server target type in the type-mapping review — a SQLite column declared INTEGER that holds text in real rows is flagged so you pick nvarchar instead of taking the declaration at face value.
  • Generated keys. Maps SQLite INTEGER PRIMARY KEY / AUTOINCREMENT (tied to ROWID) to SQL Server IDENTITY on the PK column, and reseeds with DBCC CHECKIDENT above the loaded maximum key value — so the application's next insert does not collide.
  • Dates and booleans. Detects SQLite columns that store booleans as 0/1 integers or dates as ISO-8601 text and maps them to SQL Server bit and datetime2 respectively — overridable per column when the source uses a non-standard format.
  • GUID values and Unicode. Validates SQLite text GUIDs and maps them to SQL Server uniqueidentifier on the target, and creates string columns as nvarchar so Unicode round-trips safely without the source needing a VARCHAR(n) CHARACTER SET hint.
  • Triggers, CHECK constraints, and other procedural code — outside DBConvert's scope. DBConvert's migration covers tables (with their fields, types, defaults, and indexes), views, and foreign keys. SQLite triggers, CHECK constraints, partial indexes, expression indexes, and WITHOUT ROWID table specifics stay in the source and are recreated manually in T-SQL where the equivalent feature exists (SQL Server has filtered indexes for partial-index semantics; CHECK constraints port one-for-one when the expression is portable).

Why move from SQLite to SQL Server?

Shared production database

SQLite is excellent for embedded apps, local caches, mobile apps, and single-user deployments. SQL Server is a better target when central backups, permissions, SQL Server Agent jobs, reporting, or multiple application servers become requirements.

SQL Server cloud target

The move is common when a desktop or embedded product becomes a managed application. Targets include SQL Server, SQL Server Express, Azure SQL Database, and Amazon RDS for SQL Server.

DBConvert vs SSMS imports, scripts, and GUI converters

Pick the route by whether you need a controlled import or a repeatable migration job.

Route Where it fits Where it falls short
SSMS, ODBC, linked servers, custom scripts SSMS Import / Export, OPENROWSET, .NET Controlled developer imports with hand-managed schema and type decisions. Schema cleanup, type decisions, index recreation, and validation all stay on the team.
Dedicated GUI converters General-purpose GUI table transfer. No SQLite/SQL Server-specific converter behavior, no bidirectional sync, no saved sessions reused across other database pairs.
Online file-to-SQL converters Inspection or a small SQL script generated from a .db file. No live SQL Server connection, no row-count validation, no saved settings, no synchronization jobs.
DBConvert / DBSync commercial desktop, Windows SQLite-to-SQL-Server-specific workflow with saved sessions, type-mapping review, SQL Server / Azure SQL / Amazon RDS targets, and bidirectional DBSync jobs. Commercial license; desktop tool (Windows).

Supported versions

  • SQLite 3.0 and later
  • SQL Server 2008–2022, including Express editions
  • Azure SQL Database and Amazon RDS for SQL Server
  • SQL Server schemas (dbo, custom schemas)
  • Windows authentication or SQL authentication

Supported in this path

Source SQLite
Target SQL Server
SQLite Microsoft SQL Server SQL Server Express Azure SQL Database Amazon RDS for SQL Server

Using SQLite to SQL Server Tools

When launching the DBConvert or DBSync application in GUI mode, it guides you through the steps to start database migration or synchronization:

1

Connect to SQLite source database

Specify the username/password and host/port parameters if your source database requires login credentials.

Connect to SQLite source database from DBConvert

SQLite source

Select the source .db file in the source step. DBConvert reads the tables from that file before you choose which objects to move.

2

Connect to SQL Server destination database

Specify parameters for the destination database similar to the source, defining connection settings and username/password pairs.

Connect to SQL Server target database from DBConvert

SQL Server target

Connect by TCP/IP or Named Pipes, use Azure SQL, or configure Amazon RDS for SQL Server.

Next steps: configure, validate, run

After connecting source and target, the remaining steps are the same for every database pair:

  • Configure migration options — pick tables, fields, indices, views.
  • Issue detection — the built-in checker flags integrity problems before migration starts.
  • Execute — commit the job, monitor progress, save the session for reuse.
  • Schedule and CLI — rerun saved sessions on a schedule or from the command line.
Open the full guide

Steps 3–5, software features, command-line mode, scheduler, and system requirements.

See all features