We've always counted on SQL Server as our database backend. It has served us well over the years. It isn't the cheapest part of our stack, but with the plethora of tools provided by 3rd parties, we have found an incredible and scalable method of keeping our data available and easy to maintain.

Product back end and reporting

Managing script output and input, as well as data cleansing.

Main transactional database. SQL Server 2012 Enterprise with AlwaysOn Availability Groups for high availability and disaster recovery.

Users and companies are stored in SQL Server

Integration with LOB systems.

Our beloved DB.

Back End: DataBase

社内サーバー

This is database for all Windows applications.

Stores rules for PRS

Datastorage

My go to database when working with Microsoft Technologies.

Data source from the data warehouse.

UI & administration data.

Azure SQL service to use as a main storage

for BI

Backing database for several distinct APIs

Our core systems that we integrate with are using SQL Server 2012 / 2016 database servers. We use database views on core system databases to help build our domain model.

Everyone needs a robust database, right?

Server and application metrics are all stored in InfluxDB for capacity planning and anomaly detection.

All our metrics go through InfluxDB, both applicative and system

To track time-series of course, utilizing few retention rules and continuous queries to keep time-series data fast and maintanable

InfluxDB ingests information from various sources (mostly Telegraf instances) into one place for monitoring purposes.

We use InfluxDB as a store for our data that gets fed into Grafana. It's ideal for this as it's a lightweight storage engine that can be modified on the fly by scripts without having to log into the server itself and manage tables. The HTTP API also makes it ideal for integrating with frontend services.