in2lytics LLC Information

A highly performant Time Series Database for Energy, Transportation and IoT The In2 Database is a highly scalable time series database designed to capture and store massive amounts of time series data from the Internet of Things such as AMI, SCADA and other proprietary metadata sources. Our innovation is in our fast data ingestion, pre-processing, indexing, data analytics, data visualization, information sharing and extensibility. This provides high performance read and write operations, is capable of continuous data ingestion and storage of huge volumes of data, with the ability to do real-time queries. Developed specifically for efficient integration of multi-rate, multi-source time series data, In2lytics offers significant storage, performance, flexibility, and implementation cost advantages over existing solutions. Data-driven insight needed for improved planning and decision-making capabilities. Knowledge that can be gained from grid data is critical for integrated renewables planning. It provides the insight needed to increase system availability while reducing operational expenditure. With in2lytics, the utility has the data-driven insight needed for improved planning and decision-making capabilities. Utilities in Hawaii have some of the highest penetration of distributed PV. In2lytics has been deployed at three of the local utilities, and is providing a database platform that integrates volumes of disparate data from distributed resources. In2lytics combines SCADA, AMI, irradiance, PV, Wind, and other data to provide new insights into their grid. Applications built on top of this database include modeling and forecasting, behind the meter PV estimation, customer support, curtailment and analytic applications. Results from these utilities show that the knowledge gained from the data is invaluable to understanding the impact of renewables on their grid and is giving them a complete AMI to substation view. In2lytics is a brand new time series database technology with integrated tools for data analytics, ...