LOD-a-lot democratizes the access to the Linked Open Data (LOD) Cloud by serving more than 28 billion unique triples from 650K datasets (collected in LOD Laundromat) from a single self-indexed HDT file.

This corpus can be queried online with a sustainable Linked Data Fragments interface, or downloaded and consumed locally.

LOD-a-lot overview and data flow

LOD-a-lot is easy to deploy and only requires limited resources (524 GB of disk space and 15.7 GB of RAM), enabling web-scale repeatable experimentation and research from a high-end laptop.

Read the LOD-a-lot paper

Some Statistics



524 GBs


15.7 GBs

Memory Footprint

144 seconds

Loading Time


In addition, you can download the HDT additional index to speed up SPARQL queries.

If you find LOD-a-lot interesting, please cite this work as

“Fernández, J. D., Beek, W., Martínez-Prieto, M.A., and Arias, M. LOD-a-lot: A Queryable Dump of the LOD cloud (2017). http://purl.org/HDT/lod-a-lot.”

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