Best Time Series Intelligence Software

Compare the Top Time Series Intelligence Software as of May 2025

What is Time Series Intelligence Software?

Time series intelligence software enables organizations to generate insights from raw time series data. Time series intelligence software, sometimes referred to as time series analytics software, provides features so that data teams can conduct analysis, visualize trends, forecast, and predict outcomes based on time series data. Compare and read user reviews of the best Time Series Intelligence software currently available using the table below. This list is updated regularly.

  • 1
    Trendalyze

    Trendalyze

    Trendalyze

    Decisions can't wait. Compress machine learning projects from months to minutes. Like Google, our AI search engine brings you insights instantly. Inaccuracy costs money. Patterns reveal what KPIs and averages miss. TRND uncovers the patterns that provide the early warning signs missing from the KPIs. Empower the decision maker. Trends are most relevant to decision-makers who want to know whether a threat or an opportunity is bubbling up. In the digital economy knowledge is money. TRND enables creation of sharable pattern libraries that facilitate fast learning and deployment for business improvement. If you can't monitor all, you monetize none. TRND doesn't just find needles in haystacks; it constantly monitors all needles for relevant information. If you can't afford it, you can't do it. It used to be that scale broke the bank. Our search-based approach makes micro monitoring at scale affordable.
  • 2
    Warp 10
    Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 is both a time series database and a powerful analytics environment, allowing you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system.
  • 3
    Azure Time Series Insights
    Azure Time Series Insights Gen2 is an open and scalable end-to-end IoT analytics service featuring best-in-class user experiences and rich APIs to integrate its powerful capabilities into your existing workflow or application. You can use it to collect, process, store, query and visualize data at Internet of Things (IoT) scale--data that's highly contextualized and optimized for time series. Azure Time Series Insights Gen2 is designed for ad hoc data exploration and operational analysis allowing you to uncover hidden trends, spotting anomalies, and conduct root-cause analysis. It's an open and flexible offering that meets the broad needs of industrial IoT deployments.
    Starting Price: $36.208 per unit per month
  • 4
    Amazon Timestream
    Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. Amazon Timestream saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies. Amazon Timestream’s purpose-built query engine lets you access and analyze recent and historical data together, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier. Amazon Timestream has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time.
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