Thoughtspot, Inc.

Tushar Mahale

Rakesh Kothari

Siva Singaram

Archit Bansal

Donko Donjerkovic

Simranjyot Singh Gill

Sanchit Gupta

Vishwas Sharma

Sandeep Kumar

Naresh Kumar

Jasmeet Singh Jaggi

Rahul Paliwal

Manikanta Balakavi

Rahul Manikanta Balakavi

Operating a low-latency database analysis system using domain-specific chronometry may include obtaining chronometry configuration data including chronometric instance data describing an instance of a chronometric unit of a domain-specific chronometry dataset that describes an era, such that the chronometry configuration data includes respective chronometric instance data describing each instance of the first chronometric unit of the domain-specific chronometry dataset for the era of the domain-specific chronometry dataset, generating, in the low-latency database analysis system, a domain-specific chronometry dataset in accordance with the chronometry configuration data, such that the domain-specific chronometry dataset describes a chronometric unit such that a temporal location expressed with reference to the chronometric unit and indicative of an epoch value differs from a temporal location indicative of the epoch value and expressed in accordance with a canonical chronometry, and storing the domain-specific chronometry dataset in the low-latency database analysis system.

Dynamic chronometry data orientation

A method and system may be implemented for automatically analyzing data in a database. A method for use in a low-latency database analysis system may include generating a schema. The schema may be based on a portion of an external database. The method may include storing the schema in an in-memory database. The method may include receiving a data-query. The method may include generating a resolved-request. The resolved-request may be based on the data-query and the stored schema. The stored schema may be used for executing the query on the external database. The method may include receiving results data responsive to the data-query from the external database. The method may include outputting the results data for display on a user interface.

Low-latency database analysis using external data sources

Operating a low-latency database analysis system using domain-specific chronometry may include obtaining, in the low-latency database analysis system, data expressing a usage intent with respect to the low-latency database analysis system, in response to obtaining the data expressing the usage intent, obtaining ontological data for a chronometric object in the low-latency database analysis system indicated by the data expressing the usage intent, identifying a chronometry dataset from a plurality of chronometry datasets, wherein the plurality of chronometry datasets includes a domain-specific chronometry dataset and a canonical chronometry dataset, obtaining results data in accordance with the chronometry dataset and the chronometric object, generating output data representing the results data in accordance with the chronometry dataset, and outputting the output data for presentation via a user interface.

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Milpitas, CA, United States of America

Tushar Mahale