Just a few days ago, the MapLibre community officially released the MapLibre Tile (MLT) format. This could very well be the most fundamental and hardcore technological innovation in the WebGIS domain since Mapbox defined the MVT standard a decade ago. The official announcement claims that MLT can achieve compression rates up to 6 times better than MVT and decoding speeds 3 times faster! So what exactly is MLT? Why is it positioned to challenge MVT? Let's delve into the details today.
The Benchmark: MVT Vector Tile Format
Before discussing MLT, let's first understand its "predecessor," MVT. Before the advent of MVT, viewing maps in a web browser was either through slow-loading images (raster tiles) or bulky GeoJSON files. MVT made it possible to render "vector maps" smoothly in browsers, and it serves as the data foundation for mainstream engines like Mapbox GL JS and MapLibre GL JS.
MVT is an open-source vector tile format introduced by Mapbox, based on Google's Protocol Buffers. Since its inception, it quickly became the industry standard. Its core principle involves slicing geographic data into small squares (tiles) and serializing/compressing vector data (points, lines, polygons). MVT stores the raw vector data of geographic features (coordinates and attributes of points, lines, and polygons), which can be styled and rendered in real-time after loading, supporting infinite zoom without loss of quality. MVT employs row-oriented storage, which can be understood as storing data by "feature"—first storing all attributes for "Park A," then all attributes for "Road B." By utilizing binary encoding, MVT significantly reduces tile file size, enabling faster data transmission and more efficient caching, making it particularly suitable for mobile networks and large-scale mapping applications.
What are MVT's Limitations?
With the explosive growth of geospatial data (e.g., urban 3D models, real-time trajectory data) and the adoption of next-generation GIS technologies (such as 3D maps, GPU-accelerated rendering), the limitations of MVT have become increasingly apparent:
- Strict restrictions on data types (different data types cannot appear in the same column of attributes).
- Insufficient support for 3D coordinates (elevation), making it difficult to meet the demands of 3D mapping.
- Decoding and processing efficiency does not fully leverage modern hardware capabilities (e.g., CPU SIMD instructions, GPU parallel computing).
- Lack of support for complex data types like nested properties and lists, making adaptation to new data sources (like GeoParquet) somewhat cumbersome.
It is precisely these "pain points" that have spurred the birth of MLT.
MLT: The "Upgraded Version" of MVT
MapLibre Tile (MLT) is not a minor tweak to MVT but a completely redesigned "next-generation vector tile format." It inherits MVT's core advantages while specifically addressing the aforementioned issues and introducing numerous practical new features.
First is the extreme compression ratio. MLT adopts a column-oriented storage design philosophy. A simple explanation is that while MVT stores each person's "name, age, profession" together as a bundle, MLT stores all "names" together, all "ages" together. Grouping data of the same type allows compression algorithms to perform at their maximum efficiency. For large, complex tiles, MLT's size can be up to 6 times smaller than MVT's!
Second is faster decoding speed. When parsing traditional MVT in a browser, the CPU must laboriously read and convert data piece by piece. MLT's design, however, is inherently prepared for modern graphics APIs (WebGPU) and SIMD (Single Instruction, Multiple Data). Its data structure is very close to the format preferred by graphics cards (GPUs), requiring minimal complex conversion before being sent directly to the GPU for rendering. Browser decoding speed is 2-3 times faster than with MVT.
Finally, MLT addresses many of MVT's shortcomings. It adds support for nested properties, native support for 3D coordinates (direct compatibility with elevation data, enabling 2.5D/3D basemap rendering without extra processing), and adapts to new-generation data sources by supporting linear referencing and m-values, allowing efficient integration with next-generation geographic data like Overture Maps that use the GeoParquet format.
Conclusion
Although MLT has just been released, and full adaptation by existing toolchains (like PostGIS, GDAL, Tilemaker) may take some time, MapLibre GL JS and MapLibre Native have already begun to offer support. For GIS front-end development, the future holds smaller tiles and faster parsing, allowing us to experiment with loading more complex layers containing hundreds of millions of features in web browsers. For GIS back-end, tile generation tools might undergo a wave of updates and replacements. It's essential to stay tuned to the latest developments in the MapLibre ecosystem.
MVT has been with us for a decade. The emergence of MLT heralds the arrival of a new WebGIS era characterized by higher performance, lower bandwidth consumption, and true 3D capabilities.
What are your thoughts on this new format? Feel free to share your views in the comments section!