How to Optimize PostgreSQL Cloud Costs With Tiered Storage

Timescale, a PostgreSQL-based time-series database, offers a scalable and efficient cloud storage solution by leveraging the benefits of both high-performance storage and object storage like AWS S3. The tiered storage architecture splits data into two tiers: a high-performance tier for recently accessed data and a low-cost tier for older, less-accessed data. This approach balances performance and cost, allowing users to optimize their database's scalability while reducing operational costs. By using Timescale's tiered storage system, developers can handle large datasets at petabyte scale without skyrocketing costs. The system is designed to handle various workloads, including time-series data, real-time analytics, and vector data. It also provides a mechanism for managing data retention and tiering policies, which helps prevent overburdening the high-performance tier and maintains efficient performance. Additionally, Timescale's native hybrid-row columnar storage engine can reduce disk space usage by 90%, making it an ideal solution for time-series data and challenging workloads at scale.