Robert Adin Libby

US Patent:

20200250172, Aug 6, 2020

Filed:

Jan 31, 2019

Appl. No.:

16/264407

Inventors:

- San Francisco CA, US
Michael SGROI - San Francisco CA, US
Sanjay ACHARYA - San Francisco CA, US
Robert LIBBY - San Francisco CA, US
Christopher LISH - San Francisco CA, US
Jeremiah David BRAZEAU - San Francisco CA, US

Assignee:

salesforce.com, inc. - San Francisco CA

International Classification:

G06F 16/23

Abstract:

Systems, methods, and computer-readable media for event sourcing datastores are provided. Events are sent to an event sourcing datastore (ESDS) from an external service, and the events are appended to an event log. The ESDS maintains the event log in one table and the events are automatically aggregated via streaming. The ESDS is linearly scalable, and enforces uniqueness, consistency, and user-defined constraints when appending events to the event log. The aggregate state is computed asynchronously and transparently cached, which provides increased read throughput and reduced latency. Other embodiments may be described and/or claimed.

US Patent:

20200097893, Mar 26, 2020

Filed:

Sep 24, 2018

Appl. No.:

16/139828

Inventors:

- San Francisco CA, US
Robert Libby - San Francisco CA, US
Christopher Lish - San Francisco CA, US
Benjamin Busjaeger - San Francisco CA, US
Balachandar Mariappan - San Francisco CA, US
Amanda Hatker - San Francisco CA, US

International Classification:

G06Q 10/08
G06F 17/30
G06F 9/54
H04L 29/08

Abstract:

A method of inventory data aggregation and delivery over a distributed network comprises generating inventory data with respect to plural disparate sources, and publishing that data over a distributed network to an event processor. The method further includes receiving the published inventory data through subscription to the event processor and distributing it to a plurality of requesting devices, e.g., client devices, over the distributed network. This can include aggregating and filtering by locale or product-type the inventory data in response to requests received from those devices. This can further include reducing the aggregated, filtered data to accommodate inventory reserves, e.g., of retail outlets.