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Combining merkle trees in graph databases

  • US 10,242,065 B1
  • Filed: 06/30/2016
  • Issued: 03/26/2019
  • Est. Priority Date: 06/30/2016
  • Status: Active Grant
First Claim
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1. A computer implemented method of implementing a Merkle tree having bi-directional edges to process data in a database, the method comprising:

  • defining, by a hardware processor executing a database management process, a Merkle tree with each node having a hashed value of the metadata for the node and that of any children of that node;

    associating non-hashed data with the hashed data for each node, wherein the non-hashed data comprises an initial up-pointer from a child node to any of its immediate parent node;

    defining, by the processor, a graph database using graph structures for semantic queries with nodes, bi-directional edges and properties to represent the data;

    combining the Merkle tree and graph database to define up-pointers and down-pointers comprising edges between the nodes of the Merkle tree using the bi-directional edges of the graph database to create a reference for the initial up-pointers associated with each Merkle tree node to thereby facilitate efficient traversal of the database through both the up-pointers and down-pointers, and efficient detection of any change in the database through changes in the hashed data, and wherein the bi-directional edges with the initial up-pointers along with the original Merkle tree hash scheme allows for efficient traversal of the tree where the hash values indicate non-changed nodes to prevent traversing corresponding sections of the database, and further allows efficient path definitions and data location by allowing database processes to walk up edges; and

    storing the Merkle tree in a memory coupled to the processor.

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