Contextin Powers 10 Billion Real-Time Pricing Decisions Per Day Using the Aerospike NoSQL Database and Key-Value Store
Customer Company Size
Mid-size Company
Region
- America
- Europe
Country
- European Union
- United States
Product
- Aerospike NoSQL Database
- Apache Hadoop
- MySQL
- Qlikview
Tech Stack
- NoSQL Database
- Distributed File System
- Relational Database Management System
- Data Analysis Platform
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries
- Software
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Real-Time Location System (RTLS)
Services
- System Integration
- Data Science Services
- Cloud Planning, Design & Implementation Services
About The Customer
Contextin is a performance advertising platform that aims to change the rules of conventional demand-side platforms by relying on an automated discovery engine. Unlike traditional platforms that depend on pre-determined audience criteria, Contextin's technology delves deeper into hundreds of attributes to find granular signals that influence performance. This approach allows Contextin to dynamically infer data correlations among non-traditional attributes on an impression-by-impression basis, using real-time bidding (RTB) to price and buy placements accordingly. The result is dramatically higher ad performance, optimized costs per mille, action, or click, and the ability to capture previously untapped audiences. Contextin's platform uses complex algorithms and pattern recognition to analyze more than 10 billion ad impressions daily, ensuring 100% availability and real-time delivery of data through the Aerospike NoSQL database.
The Challenge
Contextin’s unique algorithmic approach to campaign performance optimization works by analyzing hundreds of granular variables—including page characteristics, user engagement data, and semantics—on an impression-by-impression basis and then extrapolating its learning for each campaign within the context of the specific performance and budget parameters. This enables Contextin to assess bid price and identify the type of impression most likely to get results. With massive sets of proprietary data at the core of Contextin’s platform, the company recognized the need for a powerful NoSQL database that could manage and process vast sets of information without slowing RTB response times. To support its early production platform, Contextin integrated an open source distributed database to which the company was contributing code. However, as its business grew, Contextin began to evaluate NoSQL database options that would offer greater performance. Query time and availability became the stumbling blocks for many of the NoSQL databases evaluated. While many of these solutions were capable of working with significant amounts of data, few were equipped to consistently provide the millisecond response times required in the online advertising industry.
The Solution
Contextin became aware of the Aerospike real-time NoSQL database and decided to conduct a proof of concept to evaluate Aerospike’s performance. The company saw the results it needed. Aerospike demonstrated sub-millisecond latency and the ability to process queries consistently within 5 milliseconds. Moreover, it was able to horizontally scale to 100,000 QPS per each server in the cluster. Finally, as Aerospike processed large volumes of data, it did not slow or stall, thereby ensuring 100% availability. Further cementing Contextin’s decision were Aerospike’s cross data center replication functionality and responsive, knowledgeable technical support. Following the proof of concept and decision to adopt Aerospike, Contextin was able to move into full production in less than two months. Contextin now has an Aerospike database with cross data center replication deployed in each of four data centers: two on the East Coast, one on the West Coast, and another in Europe. Contextin uses the Aerospike database to respond to queries by combining real-time data with information from the other data management and business intelligence systems it has deployed. These include terabytes of unduplicated data stored in its Apache Hadoop distributed file system, MySQL relational database management system, and Qlikview data analysis platform. Aerospike’s ability to conduct read and write transactions within 5 milliseconds helps Contextin power more than 10 billion pricing decisions per day. In addition to providing reliable real-time performance, the Aerospike database automatically manages itself, minimizing the demands on Contextin’s IT team. Currently, one internal IT administrator is able to easily manage all of the company’s Aerospike deployments. Equally important is the technical support Contextin receives from Aerospike.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Infosys achieves a 5–7 percent effort reduction across projects
Infosys, a global leader in consulting, technology, and outsourcing solutions, was facing significant challenges in application development and maintenance due to its distributed teams, changing business priorities and the need to stay in alignment with customer needs. The company used a mix of open source, home-grown and third-party applications to support application development projects. However, challenges resulting from distributed teams using manual processes increased as the company grew. It became more and more important for Infosys to execute its projects efficiently, so they could improve quality, reduce defects and minimize delays.
Case Study
Arctic Wolf Envelops Teamworks with 24x7 Cybersecurity Protection and Comprehensive Visibility
Teamworks, a leading athlete engagement platform, faced rising cyberthreats and needed enhanced visibility into its network, servers, and laptops. With software developers connecting from all over the world, the company sought to improve its security posture and position itself for future growth. The company had a secure platform but recognized the need for a more proactive solution to identify gaps within its technology infrastructure. Data exfiltration and malicious access were top concerns, prompting the need for a comprehensive security upgrade.
Case Study
Sawback IT and Datto Save Client From a Costly Mistake
Ballistic Echo, a software development house, faced a critical challenge when human error led to the deletion of thousands of lines of unique code. This incident occurred before the code was pushed to source control, resulting in significant loss of time, revenue, and work. The previous file-level backup solution they used was slow and inefficient, making it nearly impossible to manually recreate the lost work. The need for a more reliable and efficient business continuity solution became evident to avoid such disasters in the future.
Case Study
Opal Helps Customers Shine Thanks to Datto
SP Flooring & Design Center faced a ransomware attack that encrypted and locked their files. The attack was initiated through a compromised service account set up by an outside vendor. The ransomware infection was isolated quickly, but there was a concern about the extent of the data at risk. The company had backups in place but was unsure of how much information was compromised. The situation required immediate action to prevent further damage and restore the affected data.
Case Study
Zapier Aggregates Multiple Analytics in a Single Dashboard with the New Relic Platform
Zapier, a company that enables non-technical users to push data between hundreds of web applications, was facing a challenge in automating and provisioning servers for optimal performance. The company's environment consisted of 50 Linux servers on the Amazon Elastic Compute Cloud (EC2), a Django application split across several servers, and a backend consisting of a dynamic number of celery task workers fed by messages published to a RabbitMQ cluster. They also maintained a number of internal web services on nginx in front of Gunicorn and Node.js processes. Redis handled simple key and value stores, with logging handled by Graylog2 and ElasticSearch. However, they realized that no level of automation would be sufficient without an effective monitoring solution in place. They needed a tool that could provide immediate alerts when something was breaking and could be easily implemented into their environment.
Case Study
Pipeline Insight Case Study: YARCDATA
YarcData faced challenges in determining the conversion rates of prospects into customers through various marketing efforts and identifying the source of its leads. They wanted to know the percentage of opportunities in the sales pipeline that came from different marketing events, web downloads, or self-sourced sales opportunities. Additionally, they needed the ability to drill down into the data to guide where to allocate more marketing dollars based on the success of previous efforts. Previously, YarcData relied heavily on spreadsheets and Salesforce.com reports, which made it difficult to extract the exact information they needed. This reliance on spreadsheets represented about 70% of their data presentation.
