OneSparse

There are open source projects moving toward this scale, the GraphBLAS for example uses an algebraic formulation over compressed sparse matrix representations for graphs that is designed to be portable across many architectures, including cuda. It would be nice if companies like nivida could get more behind our efforts, as our main bottleneck is development hardware access. To plug my project, I've wrapped the SuiteSparse GraphBLAS library in a postgres extension [1] that fluidly blends algebraic graph theory with the relational model, the main flow is to use sql to structure complex queries for starting points, and then use the graphblas to flow through the graph to the endpoints, then joining back to tables to get the relevant metadata. On cheap hetzner hardware (amd epyc 64 core) we've achieved 7 billion edges per second BFS over the

I'm extending Postgres with the GraphBLAS/SparseBLAS APIs for sparse and dense linear algebra operations directly in SQL with OneSparse. Like JSON/JSONB did for unstructured data, OneSparse does for matrices, vectors and linear algebra optimized with the SuiteSparse JIT compiler to target dense and sparse kernels for CPUs and GPUs. https://github.com/OneSparse/OneSparse

dgraph.io uses posting lists. I think the state of the art is https://github.com/GraphBLAS. Examples: https://github.com/michelp/pggraphblas & https://github.com/RedisGraph/RedisGraph/

Hi Michel - You're working on a GraphBLAS Postgres implementation [0] -- here's an open question I've been pondering... [0] Postgres GraphBLAS https://github.com/michelp/pggraphblas Now that we have SOTA linear algebra models for graphs [1], logic [2] and the lambda calculus [3] that are being optimized for vectorized parallel compute on modern CPU/GPU/TPUs -- do we have the makings for a unified linear algebra model that obsoletes the relational algebra model in relational DBs? [1] Graph Algorithms in the Language of Linear Algebra (2011) https://epubs.siam.org/doi/book/10.1137/1.9780898719918 Mathematical Foundations of the GraphBLAS (2016) https://arxiv.org/pdf/1606.05790.pdf [2] A Linear Algebraic Approach to Datalog Evaluation (2017) [pdf] https://arxiv.org/abs/1608.00139 A Linear Algebraic Approach to Logic Programming (2018) https

It's true. I look forward to seeing more language bindings, like Python, Javascript, etc. I expect it will be soon. For my own GraphBLAS education I have been working on a PostgreSQL extension: https://github.com/michelp/pggraphblas