AWS IoT Analytics vs Software AG TrendMiner comparison

Cancel
You must select at least 2 products to compare!
Ranking
3rd
out of 10 in IoT Analytics
Views
610
Comparisons
556
Reviews
0
Average Words per Review
0
Rating
N/A
5th
out of 10 in IoT Analytics
Views
85
Comparisons
47
Reviews
0
Average Words per Review
0
Rating
N/A
Comparisons
Also Known As
TrendMiner
Learn More
Overview

AWS IoT Analytics is a fully-managed service that makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build an IoT analytics platform. It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications and machine learning use cases.

IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield.

AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can setup the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing the processed data. Then, you can analyze your data by running ad hoc or scheduled queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. AWS IoT Analytics makes it easy to get started with machine learning by including pre-built models for common IoT use cases.

You can also use your own custom analysis, packaged in a container, to execute on AWS IoT Analytics. AWS IoT Analytics automates the execution of your custom analyses created in Jupyter Notebook or your own tools (such as Matlab, Octave, etc.) to be executed on your schedule.

AWS IoT Analytics is a fully managed service that operationalizes analyses and scales automatically to support up to petabytes of IoT data. With AWS IoT Analytics, you can analyze data from millions of devices and build fast, responsive IoT applications without managing hardware or infrastructure.

TrendMiner software is based on a high-performance analytics engine for data captured in time series. With TrendMiner, process engineers and operators can easily search for trends and question their process data directly – without help from a data scientist.

TrendMiner delivers all you need to analyze, monitor and predict the performance of batch, grade and continuous plants.

Sample Customers
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Total, Sitech Services
Top Industries
VISITORS READING REVIEWS
Government29%
Educational Organization16%
University11%
Computer Software Company10%
No Data Available
Company Size
VISITORS READING REVIEWS
Small Business16%
Midsize Enterprise9%
Large Enterprise75%
No Data Available

AWS IoT Analytics is ranked 3rd in IoT Analytics while Software AG TrendMiner is ranked 5th in IoT Analytics. AWS IoT Analytics is rated 0.0, while Software AG TrendMiner is rated 0.0. On the other hand, AWS IoT Analytics is most compared with ThingSpeak and Google Cloud IoT Core, whereas Software AG TrendMiner is most compared with .

See our list of best IoT Analytics vendors.

We monitor all IoT Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.