Ideal for addressing performance and scalability challenges of high-volume data ingestion, processing, retrieval, analytics, and machine learning, kdb is proven to validate and estimate sensor and smart meter data at millions of readings per second.

kdb can also aggregate billions of measurement records in seconds and store and analyze trillions of records and diverse data sources. Customers have benefited from:

• 10X to 500X improved performance.
• 90% less infrastructure cost.
• lower total operating costs with improved scalability.
• reduced time to market through proven big data technology and expertize.

Many companies today use less than 10% of the sensor data they collect. They struggle to keep up with Validation, Estimation and Editing (VEE) processes needed to support big data analytics systems because of the high volumes and velocities of data.

To combat VEE system overload, KX provides VEE and analytics capabilities to ingest, validate, estimate, and analyze massive amounts of streaming, real-time and historical data from sensors, devices, and other data sources.

kdb also enables bitemporal modelling of sensor data and attributes with nanosecond precision, enabling rapid navigation across time for continuous analytics, avoiding the need to pause, and ensuring forensic auditability and traceability of data updates.

KX is particularly useful for utilities looking to better manage DER – such as solar panels, electricity storage, electric vehicles, and other controllable loads – given the intermittency and variability of the outputs.

Integrated, continuous data analytics can also simplify situational awareness for other types of energy asset management – linking SCADA, micro-phasor and behind-the-meter data, to predict the condition of the power system and enable maintenance.

Due to its small footprint KX can provide big data analytics close to where data is collected, including on the edge, enabling utilities and solution providers to detect and predict conditions more quickly, improve availability, optimize maintenance, and increase asset longevity.

KX integrates with legacy systems and multiple data sources, for example augmenting or replacing historians and allowing for immediate customization.

Use connector frameworks to integrate with IT/OT systems, including:

• SCADA, AMI, MDM, OMS, MDM, EMS, and ADMS.
• APIs for .NET, Java, C, C++, Python, R, ODBC, MATLAB, and Excel.
• APIs for synchronizing master and reference data with other systems, including assets, locations, sensors, and sensor measurements, with built in-audit trails.

Monitoring, and proactive prevention of environmental and ecological breaches within processes can significantly reduce regulatory penalties and reputational damage.

Being able to leverage real-time insight for better use of resources, extending the effective equipment and machinery reliability, detecting breaches, reducing waste, and reducing re-work all combine to represent a measurable and credible sustainability initiative.

In addition, use 10X to 100X more efficient kdb infrastructure when compared to traditional warehouse, lake and lakehouse infrastructures for common analytics queries.