Get started with TimescaleDB on Google Axion C4A

Explore Axion C4A Arm instances in Google Cloud

Google Axion C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.

The C4A series provides a cost-effective alternative to x86 virtual machines while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.

To learn more, see the Google blog Introducing Google Axion Processors, our new Arm-based CPUs .

Explore TimescaleDB on Google Axion C4A (Arm Neoverse V2)

TimescaleDB is a high-performance, open-source time-series database built on PostgreSQL. It provides powerful features for storing, querying, and analyzing time-series data efficiently, making it ideal for IoT, telemetry, financial, and observability workloads.

TimescaleDB enables developers to handle large volumes of time-stamped data with features like hypertables, continuous aggregates, retention policies, and automated data partitioning, while maintaining full SQL compatibility.

Running TimescaleDB on Google Axion C4A Arm-based infrastructure allows you to achieve high-throughput time-series ingestion and query processing with optimized performance per watt, lower infrastructure costs, and better scalability for distributed workloads.

Common use cases include real-time monitoring of IoT sensors, event-driven analytics, DevOps metrics collection, financial time-series analysis, and building dashboards with tools like Grafana for live visualization.

To learn more, visit the TimescaleDB website and explore the TimescaleDB documentation .

What you’ve accomplished and what’s next

In this section, you:

• Explored Google Axion C4A Arm-based VMs and their performance advantages for time-series workloads
• Reviewed TimescaleDB key features, including hypertables, continuous aggregates, and retention policies
• Understood how Arm architecture enables cost-efficient, high-throughput ingestion and query processing

Next, you’ll create a firewall rule to enable remote access to the Grafana dashboard you’ll build later in this Learning Path.