Real-Time Analytics Enhancement for Adevinta with ClickHouse Cloud
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries
- Buildings
- Equipment & Machinery
Use Cases
- Real-Time Location System (RTLS)
- Time Sensitive Networking
Services
- Cloud Planning, Design & Implementation Services
- System Integration
About The Customer
Adevinta is a leading online classifieds specialist that operates more than 25 platforms across 11 countries worldwide. Their household brands include Marktplaats in the Netherlands, Mobile.de in Germany, and Leboncoin in France, reaching hundreds of millions of people every month. These platforms are all about matchmaking, and help people find whatever they’re looking for in their local communities – whether it’s a car, an apartment, a sofa, or a new job. Adevinta’s mission is to provide the best user experience for buying and selling goods and services online. They aim to create a world where people share more and waste less.
The Challenge
Adevinta, a global online classifieds specialist, operates over 25 platforms across 11 countries, reaching hundreds of millions of users monthly. Their mission is to provide the best user experience for buying and selling goods and services online. To achieve this, they needed a centralized analytics and dashboarding tool to monitor their seller's advertisements, track interactions, and improve performance in real-time. The Central Data Products team at Adevinta was tasked with building data and machine learning products to support their various marketplaces. They faced a complex challenge of needing a solution that could scale, provide end-user facing analytics capabilities with low latency and high throughput, and consider aspects such as reusability, uptime, and scalability. Adevinta required a user-facing real-time analytics and dashboarding solution that would allow the sellers to monitor their advertisements in real-time, tracking views, favorites, and likes, and capturing every interaction that occurs on their marketplaces.
The Solution
Adevinta evaluated several cloud-based database services, including ClickHouse Cloud, Google BigQuery, and Cloud Spanner. Their main requirements were a fully-fledged database service that was performant, efficient, had capabilities like indexing, disaster recovery, backup and restore, low operational complexity, managed service and easily scalable, cloud agnostic, easy to deploy and operate, rich query language, low latency, high throughput use case with <3 sec response time as the service level agreement (SLA), current production workload - 80B rows (18TBs), and highly analytical queries with SQL interface. After evaluation, they found that ClickHouse performed exceptionally well for their specific needs, as it was performant, cloud-agnostic, and more cost-effective than the other solutions. Adevinta chose ClickHouse Cloud as it fit within their budget and offered the most value for their needs. The solution was tested across multiple marketplaces with 22 queries per second, using a single table of 20 billion rows and 20 terabytes of data.
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
Smart Water Filtration Systems
Before working with Ayla Networks, Ozner was already using cloud connectivity to identify and solve water-filtration system malfunctions as well as to monitor filter cartridges for replacements.But, in June 2015, Ozner executives talked with Ayla about how the company might further improve its water systems with IoT technology. They liked what they heard from Ayla, but the executives needed to be sure that Ayla’s Agile IoT Platform provided the security and reliability Ozner required.
Case Study
IoT enabled Fleet Management with MindSphere
In view of growing competition, Gämmerler had a strong need to remain competitive via process optimization, reliability and gentle handling of printed products, even at highest press speeds. In addition, a digitalization initiative also included developing a key differentiation via data-driven services offers.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Premium Appliance Producer Innovates with Internet of Everything
Sub-Zero faced the largest product launch in the company’s history:It wanted to launch 60 new products as scheduled while simultaneously opening a new “greenfield” production facility, yet still adhering to stringent quality requirements and manage issues from new supply-chain partners. A the same time, it wanted to increase staff productivity time and collaboration while reducing travel and costs.
Case Study
Energy Saving & Power Monitoring System
Recently a university in Taiwan was experiencing dramatic power usage increases due to its growing number of campus buildings and students. Aiming to analyze their power consumption and increase their power efficiency across 52 buildings, the university wanted to build a power management system utilizing web-based hardware and software. With these goals in mind, they contacted Advantech to help them develop their system and provide them with the means to save energy in the years to come.
Case Study
Integration of PLC with IoT for Bosch Rexroth
The application arises from the need to monitor and anticipate the problems of one or more machines managed by a PLC. These problems, often resulting from the accumulation over time of small discrepancies, require, when they occur, ex post technical operations maintenance.
