Senior Software Enginer at a tech vendor with 11-50 employees
Real User
Top 20
Feb 28, 2026
In production, we use the cloud, but in other environments like development and integration, we use self-managed. We store quite a lot of data on TiDB Cloud because it is a scalable database that supports tons of data with online and offline analysis, and online transactions. Our company focuses on transportation support, with many sensors installed on cars and trucks that collect a lot of data about them. Truck owners can then use this data to analyze their cars and their business to support and grow their business. I would like to share how we calculate the speed of the car and the value of the truck, as all the CRUD operations about the data happen in TiDB Cloud.
TiDB Cloud is basically used for building scalable, high-availability databases that combine the strengths of OLTP. The main use cases would be for HTAP workloads, STAP workloads, distributed SQL systems, cloud-native databases, or large-scale databases. I have implemented it in making analytics dashboards and e-commerce platforms. I use TiDB Cloud for analytics dashboards because it supports hybrid transactional and analytical processing. You can query fresh transactional data in real-time without ETL delays. For data ingestion, applications write transaction data into TiDB Cloud. It supports the MySQL protocol, which is easy for integration. It also replicates data to TiFlash for columnar storage with OLTP queries. It has query layers and is useful for visualization tools such as Grafana, which can connect to TiDB Cloud as a data source. I have also been working on a financial payment system in my personal project. It uses high transactions, ACID consistency, and real-time fraud checks. TiDB Cloud provides strong consistency and high availability. For one of my e-commerce platforms, I used it for inventory tracking and user activity tracking for horizontal scaling. It handles sudden loads well.
PM at a manufacturing company with 10,001+ employees
Real User
Top 20
Feb 19, 2026
My main use case for TiDB Cloud is developing technical documentation related to vehicle services, such as buses and trucks for Iveco. TiDB Cloud helps with that process as it is a Content Management System, which allows me to organize all the information in a chaptering structure. I start from the Bill of Materials of the vehicle and use drawings released by engineering to develop technical documentation for owner manuals, service manuals, and similar materials.
Silverlake Axis has a core banking and loan product called SILK, used by most banks in Southeast Asia, like in Malaysia, Singapore, and Thailand. The new product I'm working on, Mobius, is a replacement for SILK, which runs on a mainframe. Mobius uses TiDB, along with Java and other frameworks.
We use an open-source tool called Prometheus. It is an available offering with extensive documentation. The primary purpose of using a time series database like Prometheus is to collect metrics of various activities. These activities can be on the user side, infrastructure side, or behind the scenes where the software is running. There is a wide variety of use cases for time series databases, mainly focused on collecting and analyzing metrics. For example, you might want to track how many active users log into your product over different periods—minutes, hours, days, weeks, or months. This data can help you understand user behavior and activity trends. Time series databases record data points over time, allowing you to recall past data or visualize current activity. This is useful for monitoring user engagement, understanding the geographic distribution of your user base, and many other metrics. We use Prometheus for collecting metrics and Grafana for visualizing them. Grafana allows us to create real-time charts and graphs that display how data changes over time. For example, if you are running an e-commerce site, you might see increased user activity in the evenings when people are more likely to shop. By combining Prometheus with Grafana, we can track events such as payment initiations on an e-commerce site. Prometheus records the events, and Grafana visualizes them, showing trends and spikes in user activity
With DBaaS, businesses can manage their databases without handling the underlying infrastructure. It offers scalability, reliability, and user-friendly interfaces, making it efficient for IT teams. DBaaS solutions streamline database management by minimizing administrative tasks. They empower organizations to swiftly scale operations and enhance their performance. Automation features reduce the need for manual intervention while ensuring high availability and seamless integration...
In production, we use the cloud, but in other environments like development and integration, we use self-managed. We store quite a lot of data on TiDB Cloud because it is a scalable database that supports tons of data with online and offline analysis, and online transactions. Our company focuses on transportation support, with many sensors installed on cars and trucks that collect a lot of data about them. Truck owners can then use this data to analyze their cars and their business to support and grow their business. I would like to share how we calculate the speed of the car and the value of the truck, as all the CRUD operations about the data happen in TiDB Cloud.
TiDB Cloud is basically used for building scalable, high-availability databases that combine the strengths of OLTP. The main use cases would be for HTAP workloads, STAP workloads, distributed SQL systems, cloud-native databases, or large-scale databases. I have implemented it in making analytics dashboards and e-commerce platforms. I use TiDB Cloud for analytics dashboards because it supports hybrid transactional and analytical processing. You can query fresh transactional data in real-time without ETL delays. For data ingestion, applications write transaction data into TiDB Cloud. It supports the MySQL protocol, which is easy for integration. It also replicates data to TiFlash for columnar storage with OLTP queries. It has query layers and is useful for visualization tools such as Grafana, which can connect to TiDB Cloud as a data source. I have also been working on a financial payment system in my personal project. It uses high transactions, ACID consistency, and real-time fraud checks. TiDB Cloud provides strong consistency and high availability. For one of my e-commerce platforms, I used it for inventory tracking and user activity tracking for horizontal scaling. It handles sudden loads well.
My main use case for TiDB Cloud is developing technical documentation related to vehicle services, such as buses and trucks for Iveco. TiDB Cloud helps with that process as it is a Content Management System, which allows me to organize all the information in a chaptering structure. I start from the Bill of Materials of the vehicle and use drawings released by engineering to develop technical documentation for owner manuals, service manuals, and similar materials.
Silverlake Axis has a core banking and loan product called SILK, used by most banks in Southeast Asia, like in Malaysia, Singapore, and Thailand. The new product I'm working on, Mobius, is a replacement for SILK, which runs on a mainframe. Mobius uses TiDB, along with Java and other frameworks.
We use an open-source tool called Prometheus. It is an available offering with extensive documentation. The primary purpose of using a time series database like Prometheus is to collect metrics of various activities. These activities can be on the user side, infrastructure side, or behind the scenes where the software is running. There is a wide variety of use cases for time series databases, mainly focused on collecting and analyzing metrics. For example, you might want to track how many active users log into your product over different periods—minutes, hours, days, weeks, or months. This data can help you understand user behavior and activity trends. Time series databases record data points over time, allowing you to recall past data or visualize current activity. This is useful for monitoring user engagement, understanding the geographic distribution of your user base, and many other metrics. We use Prometheus for collecting metrics and Grafana for visualizing them. Grafana allows us to create real-time charts and graphs that display how data changes over time. For example, if you are running an e-commerce site, you might see increased user activity in the evenings when people are more likely to shop. By combining Prometheus with Grafana, we can track events such as payment initiations on an e-commerce site. Prometheus records the events, and Grafana visualizes them, showing trends and spikes in user activity