MillenniumDB: A Multi-modal, Multi-model Graph Database Engine


Current knowledge graphs encompass diverse data formats, including images, text, tables, audio files, and videos. Additionally, the graph database ecosystem is required to support multiple coexisting data models. Addressing these challenges is essential for promoting interoperability between data sources. This demo introduces MillenniumDB, a high-performing, open-source graph database handling this diversity of data formats and models. MillenniumDB is a multi-modal, multi-model graph database, supporting the popular property graph paradigm, the Semantic Web format RDF, and the multi-layered graph model, which combines and extends the two. In terms of querying, its provides support for a Cypher-like language over property graphs and multilayered graphs, as well as SPARQL 1.1 support over RDF. The engine is build on a solid theoretical foundation and it leverages worst-case optimal join algorithms in combination with traditional relational query optimization. It also support a wide array of graph-specific tasks such as path finding, pattern recognition, and similarity search on multimodal data. In this demo, we will showcase how MillenniumDB is currently being used to host three public multi-modal knowledge graphs. The first one, a multi-layered graph called TelarKG, was developed at IMFD Chile to track the information about the Chilean constitutional reform. In the second one, called BibKG, we integrate information about Computer Science publications from different sources and make them available as a property graph. Finally, for RDF, we provide a SPARQL endpoint for Wikidata, the largest knowledge graph openly available online. We remark that our endpoints have stable links, allowing the audience to post queries using their Web browser with no restrictions, and will be available during the review process and during the demo.

In SIGMOD 2024 (Demo Track)
Sebastián Ferrada
Sebastián Ferrada
Assistant Professor

Research. Coffee. Lifting.