Firebolt > Case Studies > Infy.TV Efficiently Scales Ad Tech Analytics

Infy.TV Efficiently Scales Ad Tech Analytics

Customer Company Size

Startup

Region

America

Country

United States

Product

Firebolt
AWS Kinesis Data Firehose
AWS RDS

Tech Stack

AWS Kinesis Data Firehose
Firebolt
AWS RDS

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Cost Savings

Technology Category

Platform as a Service (PaaS) - Data Management Platforms
Analytics & Modeling - Real Time Analytics

Applicable Industries

Software
Telecommunications

Applicable Functions

Business Operation

Use Cases

Real-Time Location System (RTLS)

Services

Cloud Planning, Design & Implementation Services
System Integration

About The Customer

Infy.TV is a rapidly growing startup in the ad tech industry, focusing on helping publishers drive user engagement through intelligent content integration and monetization of streaming services. The company is known for its innovative approach to integrating content and monetizing streaming services, which has positioned it as a key player in the ad tech space. Infy.TV's primary goal is to provide publishers with the tools they need to enhance user engagement and maximize revenue from streaming content. As a startup, Infy.TV is constantly seeking ways to improve its technology stack to handle the increasing demands of data ingestion and analysis, which are critical to its operations and service offerings.

The Challenge

As a rapidly growing startup in the ad tech space, Infy.TV had been hard-pressed to build out a scalable architecture to handle frequent data ingestion and low-latency queries for their bespoke, customer-facing financial metrics dashboard. Infy.TV currently generates over 200 million records per day. Efficiently ingesting and analyzing these kinds of data volumes maxed out the capabilities of a scaled-out instance of Postgres on AWS’ RDS (Relational Database Services) offering. Ingestion from Infy.TV’s in-memory Aerospike document store into an aggregated form in RDS could only be processed once a day. The architecture for the RDS cluster simply couldn’t scale for high-performance analytical queries, and the cost of the entire setup was becoming prohibitive.

The Solution

Infy.TV turned to Firebolt for its high-performance, hardware-efficient and cloud-native scalable architecture for analytics workloads. The company established a micro-batch data ingestion pipeline into Firebolt, increasing daily ingest frequency to hourly loads. They leverage AWS Kinesis Data Firehose to orchestrate data movement to S3, with hourly ingestion pipelines defined, scheduled and executed from S3 into Firebolt. In Firebolt, Infy.TV initially set up a data retention policy of 90 days, capturing, storing and analyzing 18 billion records on a rolling basis. With some modifications to the target data model, as well as some minor tuning of Firebolt’s primary index on the primary fact table, Infy.TV established sub-second query performance on this massive dataset with little system configuration, on a very modestly sized engine. Users are now able to access deep insights into their content performance metrics via both customer visualizations and Looker dashboards.

Operational Impact

Infy.TV improved its data ingestion process by implementing a micro-batch data ingestion pipeline, allowing for hourly data loads instead of daily.
The company was able to achieve sub-second query performance on a massive dataset, enhancing the speed and efficiency of data analysis.
Users gained access to deep insights into content performance metrics through customer visualizations and Looker dashboards, improving decision-making capabilities.
The solution allowed Infy.TV to maintain a data retention policy of 90 days, managing 18 billion records on a rolling basis.
The architecture changes resulted in a more cost-effective setup, reducing the prohibitive costs associated with the previous system.

Quantitative Benefit