Lower operational costs
Simple setup and maintenance using QuestDB Docker image
Integrations with existing tools using the REST API
Real-time results despite massive throughput
Reactive support from QuestDB engineering
Reliable and fast query times for insights
Innova develops big data solutions for financial transactions, BI systems, IT infrastructure, security, and network operators. Our services include real-time analytics of the network infrastructure of the largest Telecommunications provider in Turkey.
In this case study, we summarize why Innova chose QuestDB, their migration experience, and the improvements they gained in query speed, maintainability, and compatibility.
Innova found QuestDB because of its requirements to store and analyze massive amounts of data that needs to be served to their customers quickly. The data Innova collects needs to be presented to customers so that it’s easy to understand changes over time. The search for a database that can display this kind of information in a timeline as fast as possible led to QuestDB.
Innova’s client is one of the largest telecommunications providers in Turkey, serving internet connections to over 5 million customers. Infrastructure at this scale uses massive amounts of resources and generates a tremendous volume of data. Innova uses operational data from this provider to show their customers information about their own internet connections, such as the quality of service, download speed, upload speed, bandwidth, and more.
Innova store the bandwidth data of devices in Fiber To The Home (FTTH) topology from collectors, which run on hourly intervals. These collector jobs contain time series for each device in JSON format and based on this metadata, Innova produce visualizations for their customers to have insights into their network quality. For a customer, this means that they have access to charts, tables, and line graphs so they can see the state of their connectivity for the last 30 days.
The original stack built by Innova relied on MongoDB to store connectivity information, which was convenient at first. However, it soon became apparent that MongoDB was tightly dependent on physical resources and required more powerful hardware that they were happy with allocating. Moreover, as data sets grew in MongoDB, query speeds degraded below what was acceptable for their customers.
For communicating with QuestDB, Innova uses the QuestDB Docker image for running production instances and the REST API to query data for charts and insights. On average, Innova is writing hundreds of millions of records per day while performing calculations on an ever-changing data set. Usually, Innova will keep 30 days of data in QuestDB and delete older partitions when they become less useful for actionable insights.
“QuestDB allows us to query data while writing millions of records. It is an excellent database for time series analysis and can efficiently store our data. QuestDB’s community is constantly growing and its popularity is on the rise.”
Erdem Aydemir, Innova