•1 min read•from InfoQ
Article: Time-Series Storage: Design Choices That Shape Cost and Performance
Our take
In the realm of time-series databases, the choices made in storage design can significantly influence both cost and performance. This article, authored by Nirmesh Khandelwal, delves into the foundational decisions that shape how data is organized, compressed, and partitioned. By examining these critical design elements, readers will gain insights into how to optimize their database strategies using accessible tools like PostgreSQL and Apache Parquet. Explore the measurable trade-offs that can elevate your data management practices and enhance query efficiency for your time-series applications.
Every time-series database makes a set of storage design decisions: how to lay out rows, when to compress, what to partition on. These decisions determine cost and query performance more than the choice of database itself. This article works through those fundamentals from first principles, using widely available tools like PostgreSQL and Apache Parquet to make each trade-off measurable.
By Nirmesh KhandelwalRead on the original site
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