Posted On: Dec 15, 2020
AWS IoT Analytics is a fully managed service that makes it easy to collect, pre-process, enrich, store and analyze IoT data at scale to run sophisticated analytics on massive volumes of IoT data and gain insights into how IoT devices are operating without having to worry about the complexity typically required to build an analytics platform.
Starting today, IoT Analytics will also support the Apache Parquet format, an efficient open columnar storage format to store processed data in AWS IoT Analytics data stores. Apache Parquet consumes less storage and is faster for querying large volumes of data compared to text formats such as JSON which was previously the only storage format supported for storing processed data in AWS IoT Analytics. The Apache Parquet storage format is best suited when large volumes of processed data need to be stored and queried in AWS IoT Analytics and the schema of the processed data is fixed. On the other hand, the JSON storage format is best suited to store and query smaller volumes of data in AWS IoT Analytics when the schema of the processed data is expected to evolve. To get started, use the AWS IoT Analytics console to simply choose the Apache Parquet format for your AWS IoT Analytics data store and specify a schema for the processed data that will be stored. For more information on using the Apache Parquet format in AWS IoT Analytics data stores, see the File Formats page in the AWS IoT Analytics user guide.
To get started with AWS IoT Analytics, use the Quick start feature from the AWS IoT Analytics console to create a channel, data store, pipeline and data set with a single click. You can send data from devices to AWS IoT Analytics using AWS IoT Core Rules. Visit the AWS IoT website and the AWS IoT Analytics website to learn more about AWS IoT services.
For a list of AWS IoT Analytics supported regions, visit AWS Regions.