If you've spent years in MapInfo Pro, QGIS can feel both familiar and slightly alien at the same time — the core concepts of layers, styling, and spatial queries are all there, but the tools that do the job often go by different names, or work in noticeably different ways. Whether you're exploring QGIS out of curiosity or actively planning a migration, here are five tools worth getting comfortable with early.
1. The Field Calculator MapInfo users are used to Update Column for running expressions against a table. QGIS's equivalent — the Field Calculator — does the same job but with a much larger built-in function library, including native spatial functions like $area, $length, and $geometry. It also supports creating new fields on the fly rather than requiring one to already exist, which speeds up everyday attribute work considerably.
2. The Processing Toolbox This is arguably QGIS's biggest single advantage over MapInfo out of the box: a searchable library of hundreds of geoprocessing tools — buffers, clips, intersections, dissolves, and far more — all accessible from one panel, with the ability to chain them into repeatable models via the Graphical Modeler. MapInfo users accustomed to running these operations one at a time, often via separate menus or the MapBasic window, will find the Processing Toolbox a genuine productivity jump, especially once you start saving your own custom models for recurring workflows.
3. The Layer Styling Panel MapInfo's styling is typically handled per-layer through fairly linear dialog boxes. QGIS's Layer Styling panel is more powerful but takes a bit of adjustment: symbology is rule-based and layered, supporting data-defined overrides (styling driven directly by attribute values), multiple rendering rules per layer, and live preview as you build. It's a steeper initial learning curve, but it opens up cartographic control that MapInfo's native styling tools don't offer as readily.
4. The Query Builder / Select by Expression Where MapInfo users would reach for SQL Select, QGIS offers both a similar SQL-style Select by Expression tool and, separately, the more visual Query Builder in the layer properties. The expression syntax is broadly comparable to SQL, so the transition is fairly gentle, but QGIS also layers in built-in spatial predicates (intersects, contains, within, and so on) directly in the same expression builder — handy for combining attribute and spatial logic without needing separate steps.
5. DB Manager (for PostGIS connections) If you're managing shared or larger datasets, DB Manager is QGIS's built-in tool for connecting to spatial databases like PostGIS directly — browsing tables, running SQL, and adding layers straight from the database rather than working off static files. For teams moving away from individually-edited MapInfo TAB files toward a proper shared database, this is often the single biggest workflow shift, and one well worth exploring early even if you're not ready to fully commit to PostGIS yet.
Getting comfortable with the shift None of these tools are difficult once you've used them a few times — the real adjustment is unlearning MapInfo's menu structure and trusting that QGIS's tools, while organised differently, generally do more with less clicking once you know where to look. If you're planning a full migration, working through these five in a hands-on session tends to be the fastest way to build real confidence.
Want hands-on guidance?
JPS Services runs instructor-led QGIS training courses designed specifically to help MapInfo and ArcGIS users make the switch — covering everything from loading and styling data through to queries, analysis, and producing print-ready maps. Find out more about our QGIS training courses →

​If you're using QGIS day to day, there's a good chance your data lives in shapefiles or file geodatabases. That works fine — until it doesn't. As datasets grow, teams grow, and projects get more complex, a lot of GIS users hit the same wall: file-based formats simply aren't built for multi-user editing, large-scale analysis, or serious data integrity. That's where PostgreSQL and its spatial extension, PostGIS, come in.

​PostgreSQL is a mature, open-source relational database. PostGIS extends it with spatial data types, spatial indexing, and a huge library of spatial functions — everything from ST_Intersects to ST_Buffer to topology validation. In practice, this means you can store millions of features in a single table and query them with genuine SQL power: joins, aggregations, spatial filters, all running server-side rather than choking your desktop machine.

QGIS talks to PostGIS natively — no plugins required. Once you connect, you get:

• Multi-user editing. Several people can edit the same dataset at once without the file-locking headaches of shapefiles or the single-writer limits of file geodatabases.
• Faster performance on big datasets. Spatial indexes mean QGIS only pulls back what's actually in view, rather than loading an entire layer into memory.
• Version control and data integrity. Constraints, triggers, and referential integrity live in the database, not scattered across loosely-linked files.
• A single source of truth. Instead of five copies of a "final_v3" shapefile floating around a shared drive, everyone points at the same live table.
• SQL-driven analysis inside QGIS. The DB Manager and Query Builder let you write spatial SQL directly, and virtual layers let you build views without duplicating data.

​Say you're managing forestry compartment boundaries across several sites. Store them in PostGIS, and every analyst on the team edits against the same live dataset. Run a spatial join to flag compartments within a buffer of a watercourse, and the query executes in the database — QGIS just renders the result. No manual exports, no mismatched copies, no "which version is current" confusion.

​The learning curve is real but not steep: it's mostly a matter of getting comfortable with basic SQL and understanding how spatial indexes work. Once that clicks, most users don't go back to file-based workflows for anything beyond quick one-off projects.

If you'd rather learn this properly than piece it together from blog posts, JPS Services runs a full-day PostgreSQL & PostGIS training course for GIS analysts — from the fundamentals through to spatial queries you can put to work in QGIS straight away. Please complete the enquiry form for more information.