What database is used on Google TPU servers?

The Google TPU (Tensor Processing Unit) servers are designed to accelerate machine learning workloads, particularly those using the TensorFlow framework. The data used by these workloads can be stored in a variety of databases, depending on the specific requirements of the application.

Some of the databases that are commonly used with Google TPU servers include:

1. Google Cloud Storage: This is a scalable and highly available object storage service that can be used to store large datasets and other data used in machine learning workflows.

2. Google Cloud Bigtable: This is a fully managed, high-performance NoSQL database that is well-suited for use cases that require low-latency and high-throughput access to large datasets.

3. Google Cloud SQL: This is a fully managed relational database service that is compatible with several popular database management systems, including MySQL, PostgreSQL, and SQL Server.

4. Google Cloud Spanner: This is a globally distributed, scalable relational database service that is designed to provide strong consistency and high availability for mission-critical applications.

Overall, the specific choice of database used on Google TPU servers will depend on the requirements of the particular machine learning workload and the data it uses. Google Cloud provides a wide range of database options to meet the needs of different use cases.