We are tracking because we have an integrated system. We have some integration with external third parties. We also track the data that we get from external sources. In Postgres, we can handle maybe ten million records per month. We use partitioning and healing features to manage this growth in data. Google Cloud SQL provides fast and very short transactions when modifying our data, using Postgres as our database system across multiple ports. It performs queries for data and handles purchases based on those queries. The scalability with Postgres is impressive. Currently, we are in a beta phase, utilizing three instances. There were issues with write and read instances. Also, there were delays in data synchronization between the write and read columns. When data is written to the write instance, it's not always immediately available in the read instance, causing a delay of up to 20 seconds. We have the right systems to manage the necessary operations. Sometimes, we have one instance for handling requests; at other times, we might have more than two instances. Querying the correct data is fast. However, read queries can be slower due to the large amount of data they need to process. We use additional processing power from more instances to accommodate the required scale. Google Cloud SQL is straightforward. The setup and configuration are easy, and managing the team is simple. We have one dedicated person per week to handle incidents or disturbances in the process and perform additional work. It's enough for maintenance and support. As data accumulates, it's crucial to devise a strategy for managing its volume, which involves using historical tables, archiving, or partitioning. These methods are all useful. As the data volume increases, query execution times can slow down. Therefore, it's imperative to implement an effective indexing strategy. By optimizing indexes, partitioning, and other techniques, queries can be executed more efficiently, even when querying on multiple parameters. There could be two or three read instances. The synchronization between the write and the read is very fast. There are multiple advantages to Google Cloud SQL. Firstly, it operates in the cloud, making it accessible from anywhere. Unlike competitors, Google Cloud SQL is fully integrated into the cloud environment. You can quickly scale your resources up or down according to your needs, growing or decreasing. This flexibility allows you to stay aligned with current demands while optimizing costs. Overall, I rate the solution a nine out of ten.
