The developers have been working on a graph database called RedisGraph that uses linear algebra to perform operations on large graphs in sub-second time. After nearly two years of development, the first version of RedisGraph has been released as a Redis module, implementing GraphBLAS sparse matrices for internal data representation and using Cypher as its query language. The use of matrix representations allows RedisGraph to solve traditional graphing problems efficiently, with space complexity governed by the number of non-zero elements in the compressed sparse column (CSC) form used to encode the matrices. This encoding is highly space-efficient and allows database operations to be executed as algebraic expressions without needing to translate data out of its form. The performance results achieved on real data sets have been promising, with testing yielding sub-second time for graph operations on large datasets.