Why Google My Maps Has a 2,000 Location Limit (And What to Do About It)
Hit the Google My Maps location limit? Learn why it caps at 2,000 pins per layer and discover workarounds to map larger datasets.
The Google My Maps location limit is 2,000 features per layer, with a maximum of 10,000 total features per map. If you need to map more locations than this, you'll need to either split your data across multiple maps, use the Google Maps JavaScript API, or switch to a database-first approach like Notion with unlimited storage and export capabilities.
If you've ever tried to import a large dataset into Google My Maps, you've likely hit this invisible wall. The moment your spreadsheet exceeds 2,000 rows, the import fails silently or truncates your data without warning. This limitation has frustrated travelers, researchers, real estate professionals, and anyone else trying to visualize substantial location data. Understanding why this limit exists and how to work around it can save you hours of troubleshooting.
Understanding the Google My Maps Location Limit
Google My Maps enforces several strict limitations that compound quickly. Each layer in your map can contain a maximum of 2,000 features, whether those are points, lines, or polygons. You're also limited to 10 layers per map, with a total cap of 10,000 features per map regardless of how you distribute them across layers. In practice, managing multiple layers becomes unwieldy fast, especially when you need to update or filter your data.
The import process itself adds another constraint. Google's documentation explicitly states: "Do not import files with more than 2,000 rows." When uploading a CSV or spreadsheet that exceeds this limit, users report that the import either fails or truncates data without clear warning. You might not notice missing locations until you're searching for a specific place that should be there but isn't.
Why These Limits Likely Exist
Google My Maps was designed as a lightweight tool for casual users creating simple custom maps. It runs in the browser, rendering markers on the client side without the sophisticated clustering or lazy-loading that professional mapping applications use. Loading thousands of markers simultaneously could slow the interface significantly, particularly on mobile devices.
There's also a business consideration at play. Google offers enterprise mapping solutions through Google Maps Platform, which charges based on usage. The free My Maps product serves as an entry point, and Google likely has little incentive to make it powerful enough to compete with their paid offerings.
Storage and processing costs factor in as well. Every custom map lives on Google's servers, and supporting unlimited locations for millions of free users would require substantial infrastructure investment.
Practical Workarounds for the 2,000 Pin Limit
When you need to map more than 2,000 locations, several strategies can help. The most straightforward approach is splitting your data across multiple layers within a single map. If you have 5,000 coffee shops to map, you might create layers by region, category, or any other logical division. This keeps everything in one shareable map while staying under the per-layer limit.
For truly large datasets, you'll need multiple maps entirely. Some users create a "master index" map that links to regional sub-maps, though this fragments the experience and makes searching across your full dataset impossible. It's a workaround, not a solution.
Another option is filtering your data before import. Do you really need all 10,000 locations visible at once? Perhaps you can import only the highest-priority items, or create separate maps for different time periods or categories that you'll view independently.
If you're comfortable with code, the Google Maps JavaScript API removes the 2,000 limit entirely, but requires building a custom application and paying for API usage above the free tier. This is overkill for most personal projects but becomes viable for businesses with mapping at their core. For developers interested in building custom map solutions, our guide to building custom map websites with GeoJSON covers the technical approach.
When Notion Becomes the Better Foundation
Notion databases have no practical limit on the number of records you can store. A single database can hold tens of thousands of locations with the Place property, complete with coordinates, addresses, and any additional fields you need. The limitation shifts from storage to visualization. If you're new to Notion's location features, our complete guide to the Notion Place property explains how to get started.
This is where Notion to Maps enters the picture. By connecting your Notion database, you can visualize all your locations on an interactive map regardless of how many you have. The map uses clustering to handle large datasets gracefully, grouping nearby markers at lower zoom levels and revealing individual points as you zoom in. There's no need to split your data across layers or maintain multiple maps.
The workflow also differs fundamentally. With Google My Maps, your data lives in the map itself, making updates tedious. With Notion as your foundation, the database is your single source of truth. Add a new location in Notion, and it appears on your map automatically. Update an address, and the change propagates without re-importing anything. For tips on managing large location databases, see our guide on organizing 100+ locations in Notion.
Making the Switch
If you're currently bumping against Google My Maps limits, consider whether your workflow would benefit from a database-first approach. Notion excels when you need to track additional information beyond just locations, when multiple people need to collaborate on the data, or when you want to filter and organize locations using properties like status, category, or date.
The export capabilities matter too. Notion to Maps lets you download your locations as KML for Google Earth, GPX for GPS devices, GeoJSON for web mapping, or CSV for spreadsheets, meaning you can still bring your data into Google Earth, GPS devices, or any other tool that accepts standard formats. You're not locked into any single ecosystem.
For datasets under 2,000 locations that rarely change, Google My Maps remains a perfectly adequate free tool. But the moment you find yourself fighting its limitations, splitting data across layers, or maintaining multiple maps that should really be one, it's worth exploring alternatives that scale with your needs rather than constraining them.
Frequently Asked Questions
What is the maximum number of pins in Google My Maps?
Google My Maps allows a maximum of 2,000 features (pins, lines, or polygons) per layer, with up to 10 layers per map. The absolute maximum is 10,000 features per map total. However, performance degrades significantly before reaching these limits, especially on mobile devices.
Can I export Google My Maps to GPX?
Google My Maps exports to KML format natively, not GPX. To convert to GPX for GPS devices, you'll need to export as KML first, then use a conversion tool like GPS Visualizer or GPSBabel. Alternatively, if your data is in Notion, you can export directly to GPX without conversion steps.
How do I work around Google My Maps limitations?
The main workarounds are: splitting data across multiple layers (up to 10 per map), creating multiple linked maps for very large datasets, filtering data before import to show only essential locations, or switching to a database-first approach like Notion that has no location limits and supports export to multiple formats.
Why does Google My Maps truncate my data on import?
Google My Maps silently truncates imports exceeding 2,000 rows per layer. There's no error message - the import appears successful but only the first 2,000 rows are included. Always verify your location count after import, especially with large datasets.
Is there a free alternative to Google My Maps without location limits?
Notion combined with Notion to Maps offers unlimited location storage in the free tier. While Google My Maps caps at 2,000 per layer, Notion databases can hold tens of thousands of places. The tradeoff is that visualization requires connecting to an external tool rather than being built-in.