Combining merkle trees in graph databases

A method of implementing a graph database having hash-encoded nodes to process data in a database, comprising:

• defining, by a hardware processor executing a database management process, a graph database using graph structures for semantic queries with nodes, bi-directional edges and properties to represent the data;
• labeling each node with the hashed value of the node and any children to integrate a Merkle tree structure into the graph database;
• labeling each node with initial up-pointers to the node's parent node;
• wherein the integrated Merkle tree and graph database 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, 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.

A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein, the computer-readable program code adapted to execute a method of implementing a Merkle tree in a graph database to process data in a database, 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, 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.