Abstract: A computer-implemented method for updating a virtual RDF graph database, the virtual database comprising tuples including a file storage having a durability property of ACID property and guarantying consistent write, providing a virtual RDF graph database including a first RDF graph database updatable by streams and a second read-only RDF graph database stored on the file storage and updatable by batches, a catalog for storing metadata describing the second read-only RDF graph database on the file storage, the catalog being compliant with ACID and obtaining a stream of tuples and a batch of tuples, applying the stream of tuples on the first RDF graph database, applying the batch of tuples on the second RDF graph database by computing a snapshot of the second RDF graph database, including the batch of tuples, the computed snapshot and registering the computed snapshot in the catalog.

Abstract: A computer-implemented method for updating a virtual RDF graph database, the virtual database comprising tuples including a file storage having a durability property of ACID property and guarantying consistent write, providing a virtual RDF graph database including a first RDF graph database updatable by streams and a second read-only RDF graph database stored on the file storage and updatable by batches, a catalog for storing metadata describing the second read-only RDF graph database on the file storage, the catalog being compliant with ACID and obtaining a stream of tuples and a batch of tuples, applying the stream of tuples on the first RDF graph database, applying the batch of tuples on the second RDF graph database by computing a snapshot of the second RDF graph database, including the batch of tuples, the computed snapshot and registering the computed snapshot in the catalog.

Abstract: The databases and methods disclosed herein reduce costly dictionary access (writes and reads) by storing data directly in an index (e.g., storing literal values or taking advantage of Universally Unique Identifiers (UUIDs)), thereby saving time and memory. One example embodiment is a database that includes a dictionary and an index. The dictionary stores associations between keys and data. Each entry in the index includes a plurality of values corresponding to data. A value of the index includes either (i) a direct representation of corresponding data for certain data types, or (ii) a hash of the corresponding data for other data types. The hash is used in the dictionary as a key associated with the corresponding data.

Abstract: The databases and methods disclosed herein reduce costly dictionary access (writes and reads) by storing data directly in an index (e.g., storing literal values or taking advantage of Universally Unique Identifiers (UUIDs)), thereby saving time and memory. One example embodiment is a database that includes a dictionary and an index. The dictionary stores associations between keys and data. Each entry in the index includes a plurality of values corresponding to data. A value of the index includes either (i) a direct representation of corresponding data for certain data types, or (ii) a hash of the corresponding data for other data types. The hash is used in the dictionary as a key associated with the corresponding data.