IoT - Streaming Analytics - Use Cases

Case study: PRIMEX

Many IoT companies providing home connected devices are losing money due to the high cost of moving and managing data to the cloud. Primex found themselves in this situation, relying on a pay-as-you-go, serverless architecture that proved to be inefficient and expensive when deployed at Internet Scale on a continuous event stream.

SQLstream turned the tables by reimplementing their AWS Lambda functions as continuous SQL queries and reducing infrastructure and processing costs by 2/3rds, restoring Primex’s weather monitoring service to profitability.

SQLstream solves challenges of wrangling, analyzing, and acting upon IoT data in real time

Capitalizing on the richness of IoT data is compelling, but in order to yield actionable insight, data needs to be collected, ingested, analyzed, and pushed into action in continuously, and in real time. Building and managing a system able to support this kind of performance, productivity, and responsiveness is more often than not a non-secure, expensive, and slow exercise. And when the parameters change, it’s back to square one.

the challenges of wrangling, analyzing, and acting upon IoT data in real time

Real-time IoT data wrangling

Many data sources
Collection and data transport not secure
Many data formats
Variable bandwidth conditions
Data volumes are volatile
Volume too high for real-time responsiveness
Not all data is relevant
Interruptions

Streaming IoT data analytics

Results take too long
Results are not easy to access
Results are accessible to the deeply technical
Development takes a long time
Development is dependent on skill sets
Data manipulation cannot be done on-the-fly

Real-time ACTIONS

Data visualization is not real-time
Visualizations are not easily consumable
Not able to trigger alerts or actions in real-time

our solution

A COMPLETE IoT STREAMING SQL processing platform

Guavus SQLstream supports IoT stream processing at all levels of the data lifecycle through a SQL-based data wrangling, streaming analytics and automated actions platform that is easy to use by developers and analysts alike.

Guavus SQLstream combines raw IoT data (sensor, network, transaction records, social media) and stored data (personal history, network and security data, demographics, research data) to optimize operations by detecting system threats, monitoring and integrating all processes in real time, and automatizing actions. In parallel, revenue can be increased through support of multiple applications, millions of users and subscription-based aggregated feeds.