PingThings

Manage massive utility sensor data with a high-performance platform featuring 10,000x faster queries and integrated AI for real-time anomaly detection.

Paid data analysis

About PingThings

PingThings offers PredictiveGrid™, a sophisticated platform engineered for the extreme data demands of the modern power utility industry. As grid sensors like AMI and synchrophasors generate billions of data points, traditional databases often struggle with the sheer volume and velocity of information. PredictiveGrid addresses this by providing a horizontally scalable architecture that centralizes all sensor data, allowing users to move beyond simple real-time monitoring to perform deep historical analysis across their entire data history without performance degradation. The technical capabilities of the platform focus on high-throughput and intelligent data contextualization. It can process tens of millions of data points per second per node, ensuring that even the largest sensor fleets are supported. Beyond raw measurements, the system integrates metadata, geospatial data, and network topology to provide a comprehensive physical view of the grid. This multi-dimensional approach ensures that data is not just stored as numbers, but as actionable information linked to specific assets and locations in the real world. For engineers and data scientists, the platform provides a robust environment for building custom analytics and machine learning models. It supports standard open-source AI tools for tasks like anomaly detection and predictive maintenance. A standout feature is the low-code analytical application framework, which enables users to build secure, web-based Python applications without needing a background in front-end development. This allows technical teams to rapidly prototype and deploy tools that translate raw grid data into operational decisions. What distinguishes PingThings is its specialized focus on utility-scale time series data combined with enterprise-grade governance. Common data access patterns are accelerated by 10,000x, significantly reducing the time required for complex research and operational reporting. By offering both cloud and on-premise deployment options, the platform provides the flexibility needed for sensitive infrastructure environments. It bridges the gap between massive data ingestion and collaborative business intelligence, making it a critical tool for the next generation of grid management.

PingThings pros & cons

Pros

Capable of reading and writing tens of millions of data points per second per node.
Accelerates common data access patterns by 10,000x over standard speeds.
Supports integrated geospatial and network topology data for physical context.
Allows data scientists to create web applications using Python without front-end skills.
Integrates with best-of-breed open source AI tools for anomaly detection.

Cons

Pricing is not publicly disclosed and requires a direct request for a demo.
The platform requires specialized domain knowledge in utility sensor data to use effectively.
Details regarding specific cloud provider support are not available in public documentation.

PingThings use cases

Grid data scientists can use Python-based frameworks to build and deploy custom anomaly detection apps for power lines.
Utility engineers can integrate SCADA and AMI data with geospatial info to visualize grid health in a real-world physical context.
Operations managers can leverage the 10,000x query acceleration to perform historical analysis on billions of sensor readings in seconds.
Collaborative research teams can securely share sensor data and analytical findings across global locations using built-in governance tools.

PingThings features

data governance and collaboration
custom grafana dashboards
ai/ml anomaly detection
geospatial and topology mapping
python-based app development
10,000x query acceleration
10m+ points per second throughput
predictivegrid™ time series platform

PingThings pricing

Is PingThings free? No, PingThings doesn't offer a free plan.

Enterprise

Price varies

PredictiveGrid™ Platform access
Extreme read and write performance
10,000x query acceleration
Python-based analytical app development
Geospatial and topology integration
AI/ML anomaly detection
Custom Grafana dashboards
Data collaboration and governance
Support for 10M+ points per second
API access

PingThings FAQs

What types of sensors does the PredictiveGrid platform support?

The platform supports virtually all types of grid sensors, including transmission and distribution synchrophasors, digital fault recorders, and smart meter/AMI. It also handles data from SCADA systems, power quality monitors, and continuous point-on-wave sensors.

How does the platform handle extremely high-frequency data?

PredictiveGrid is built for extreme performance, capable of reading and writing tens of millions of data points per second per node. It utilizes a horizontally scalable architecture to ensure performance remains high as sensor fleets grow.

Can I build my own analytical tools on top of the data?

Yes, the platform includes a low-code framework that allows engineers and data scientists to build custom web-based analytical applications using Python. This eliminates the need for front-end engineering support when deploying new grid applications.

Does the platform support machine learning and AI analysis?

PredictiveGrid integrates with best-of-breed open-source ML and AI tools for tasks like anomaly detection and prediction. Users can apply these models to both real-time measurements and historical all-time data.

Ratings & reviews

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