Software Alternatives, Accelerators & Startups

AWS IoT Analytics VS Streamdata.io

Compare AWS IoT Analytics VS Streamdata.io and see what are their differences

AWS IoT Analytics logo AWS IoT Analytics

IoT Management

Streamdata.io logo Streamdata.io

Streamdata.io provides a proxy-as-a-service that turns any request-response REST APIs into an event-driven streaming API.
  • AWS IoT Analytics Landing page
    Landing page //
    2022-02-05
  • Streamdata.io Landing page
    Landing page //
    2023-04-02

AWS IoT Analytics features and specs

  • Scalable
    AWS IoT Analytics automatically scales to support large volumes of IoT data, accommodating billions of messages from millions of devices without the need for extensive infrastructure management.
  • Integration
    Seamlessly integrates with other AWS services like AWS Lambda, Amazon S3, and Amazon QuickSight for extended functionality and complete data processing and visualization workflows.
  • Time-series analysis
    Designed specifically to handle time-series data, providing tools and pre-built functions to analyze and visualize trends over time, which is crucial for monitoring IoT devices.
  • Data Enrichment
    Enables the enrichment of IoT data by integrating external data sources and using metadata, allowing for more contextual and meaningful data insights.
  • Machine Learning Support
    Supports integration with AWS's machine learning services, allowing users to build, train, and deploy models for predictive analysis directly on their IoT data.

Possible disadvantages of AWS IoT Analytics

  • Complexity
    The broad feature set and integration options can lead to a steep learning curve for users unfamiliar with AWS services and IoT analytics workflows.
  • Cost
    While offering extensive capabilities, the cost of using AWS IoT Analytics can become significant, especially as data volumes and processing needs increase.
  • Dependency on AWS Ecosystem
    Requires reliance on the AWS ecosystem, which can be a limitation for organizations using multi-cloud strategies or those wanting to maintain vendor neutrality.
  • Latency
    Although designed for handling IoT data, there can be latency issues in data processing and analysis, especially with high-frequency data ingestion.
  • Security Complexity
    Managing security and ensuring compliance can be complex due to the sensitive nature of IoT data and the need to configure various AWS security settings properly.

Streamdata.io features and specs

No features have been listed yet.

AWS IoT Analytics videos

AWS IoT Analytics - How It Works

More videos:

  • Review - Learn Step by Step How iDevices Uses AWS IoT Analytics - AWS Online Tech Talks

Streamdata.io videos

No Streamdata.io videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to AWS IoT Analytics and Streamdata.io)
Analytics
83 83%
17% 17
Big Data
0 0%
100% 100
Data Dashboard
100 100%
0% 0
IoT Platform
100 100%
0% 0

User comments

Share your experience with using AWS IoT Analytics and Streamdata.io. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing AWS IoT Analytics and Streamdata.io, you can also consider the following products

ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

AWS IoT - Easily and securely connect devices to the cloud.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Countly - Product Analytics and Innovation. Build better customer journeys.

OpenZoo - OpenZoo is an open-source, distributed, stream and batch processing framework.