What is Azure Time Series Insights?

Time Series Insights is built for storing, visualizing, and querying large amounts of time series data, such as that generated by IoT devices. If you want to store, manage, query, or visualize time series data in the cloud, Time Series Insights is likely right for you.

If you are building an application, either for internal consumption or for external customers to use, Time Series Insights can be used as a backend for indexing, storing, and aggregating time series data. You can build a custom visualization and user experience on top. Time Series Insights exposes REST Query APIs to enable this scenario.

If you are unsure if your data is time series, here is what you should know. Time series data represents how an asset or process changes over time. It’s unique in that it has a timestamp and time is most meaningful as an axis. Time series data typically arrives in time order and is usually treated as an insert rather than an update to your database. Because Time Series Insights captures and stores every new event as a row, change is measured over time, enabling you to look backward and to predict future change. In large volumes, storing, indexing, querying, analyzing, and visualizing time series data can be challenging.

Primary scenarios

  • Storing time series data in a scalable way.

    • At its core, Time Series Insights has a database designed with time series data in mind. Because it is scalable and fully managed, Time Series Insights handles the work of storing and managing events.
  • Near real-time data exploration.

    • Time Series Insights provides an explorer that visualizes all data streaming into an environment. Shortly after connecting an event source, event data can be viewed, explored, and queried within Time Series Insights. The data is useful for validating whether a device is emitting data as expected and monitoring an IoT asset for health, productivity, and overall effectiveness.
  • Root-cause analysis and anomaly detection.

    • Time Series Insights has tools like patterns and perspective views to conduct and save multi-step root-cause analysis. Further, Time Series Insights works in conjunction with alerting services like Azure Stream Analytics, so alerts and detected anomalies can be viewed in near real-time in the Time Series Insights explorer.
  • A global view of time series data streaming from disparate locations for multi-asset/site comparison.

    • You can connect multiple event sources to a Time Series Insights environment. This means that data streaming in from multiple, disparate locations can be viewed together in near real-time. Users can take advantage of this visibility to share data with business leaders and to enable better collaboration with domain experts who can apply their expertise to help solve problems, apply best practices, and share learnings.
  • Building a customer application on top of Time Series Insights.

    • Time Series Insights exposes REST Query APIs, enabling you to build applications that use time series data.

Capabilities

  • Get started quickly: Azure Time Series Insights requires no up-front data preparation. Connect to millions of events in your Azure IoT Hub or Event Hub in minutes. Once connected, visualize and interact with sensor data to quickly validate your IoT solutions. You can interact with your data without writing code. There is no new language to learn; Time Series Insights provides a granular, free-text query surface for advanced users, and point and click exploration.
  • Near real-time insights: Time Series Insights can ingest millions of sensor events per day, with one minute latency. Time Series Insights helps you gain insights into your sensor data by helping you spot trends and anomalies, conduct root-cause analyses, and avoid costly downtime. By enabling cross-correlation between real-time and historical data, Time Series Insights helps you unlock hidden trends in the data.
  • Build custom solutions: Embed Azure Time Series Insights data into your existing applications, or create new custom solutions with Time Series Insights REST APIs. Create personalized views you can share for others to explore your insights.
  • Scalability: Time Series Insights is designed to support IoT at scale. It can ingress from 1 million to 100 million events per day, with a default retention span of 31 days. You can visualize and analyze live data streams in near real-time, alongside historical data. Moving forward, ingress and retention rates will increase to accommodate enterprise scale.

Getting started

Getting started takes less than 5 minutes.

  1. To get started, provision a Time Series Insights environment in the Azure portal.
  2. Connect an event source like an Azure IoT Hub or Event Hub.
  3. Upload reference data (this is not an additional service).
  4. See your data in minutes with the Time Series Insights explorer.

Time Series Insights explorer

This diagram shows an example of time series insights data viewed through the explorer: Time Series Insights explorer

Next steps