Lower Latency Graph Queries in Cypher with Redis GraphRoi Lipman, Redis LabsTim Davis, Texas A&M U

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redbar0n · 2023-01 · Strong recommendation

> If you want to be my hero, find a way to fix this problem: [LINK] Let me (try to) be your hero, Marzi. (Insert favorite reference to famous cheezy pop music song, if you like.) Couldn't you use GraphBLAS algorithms, like they do in RedisGraph (which supports Cypher, btw) to fix that problem with "death star" queries? Those algorithms are based on linear algebra and matrix operations on sparse matrices (which are like compressed bitmaps on speed, re: [LINK] ). The insight is that the adjacency list of a property-graph is actually a matrix, and then you can use linear algebra on it. But it may require the DB is built bottom up with matrices in mind from the start (instead of linked lists like Neo4j does). Maybe your double array approach in RageDB could be made to fit.. I think you'll find this presentation on GraphBLAS positively mind-blowing, especially from this moment: [VIDEO] Such math-based algorithms seem perfect to optimally answer unbounded (death) star queries like “How are you connected to your neighbors and what are they?” That way, for such queries one doesn't have to traverse the graph database as a discovery process through what each node "knows about", but could view and operate on the database from a God-like perspective, similar to table operations in relational databases. Further reading: [LINK]

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michelpp · 2018-12 · Strong recommendation

Thanks for this link, very interesting talk from the graphblas author: [VIDEO] I've never seen any advantage to graphdbs over relational models until I saw this talk. Raising graph analysis to the level of linear algebra is brilliant.

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espeed · 2018-09 · Recommendation

On a related note, this upcoming paper on succinct graph representations will be presented at PACT next month ( [LINK] ) -- it's more data model than database, but I think you'll find it interesting... Log(Graph): A Near-Optimal High-Performance Graph Representation [pdf] [LINK] For something more database specific, check out the new RedisGraph module [1] implemented with GraphBLAS [2] by the venerable Tim Davis [3] himself, who as you know implements the underlying sparse matrix algos used in everything from MATLAB to Google Maps... RedisGraph in the Language of Linear Algebra with GraphBLAS, co-presented by RedisLabs and Tim Davis [video] [VIDEO] GraphBLAS is not Redis-specific, but the Redis data structures and new modular design made it an ideal candidate for the first popular database implementation. This is significant because GraphBLAS is more than 10 years in the making, the culmination of the initial D4M matrix model design by Jeremy Kepner [4] and his team at MIT Lincoln Laboratory Supercomputing Center. And for the last ~5 years or so the software model has been designed in collaboration with hardware teams at Intel, NVIDIA, IBM, and the labs [5] to make chips and architectures optimized for these new matrix models and capable of exascale. It all came together this summer with the release of GraphBLAS 1.0 [6]. Now that GPU and TPU accelerators are populating the data centers and linear algebra has come en vogue, hopefully enough software engineers will be ready wit

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