Transform PostgreSQL into a Columnar Database Using Citus

Columnar databases are transforming the way we handle large datasets by storing data in columns rather than rows. This approach enhances performance, especially for analytical queries, by allowing faster data retrieval and efficient storage. As businesses generate more data than ever, understanding the benefits of columnar databases becomes crucial. In this blog, we'll explore how these databases work, their advantages over traditional row-based systems, and why they are becoming a popular choice for data-driven organizations.
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Using pg_upgrade to Upgrading Your PostgreSQL Cluster on Windows

Upgrading your PostgreSQL cluster is an important task to keep your database running smoothly and securely. With each new release, PostgreSQL introduces performance improvements, security patches, and new features that can benefit your system. However, upgrading can be a bit tricky, especially if you're working in a Windows environment, where certain challenges like permissions, service management, and file handling may differ from Linux setups. In this blog, we’ll walk you through the process of performing an upgrade on a PostgreSQL cluster in Windows, covering the key steps to ensure everything goes smoothly without causing data loss.
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Optimizing PostgreSQL with Composite and Partial Indexes: A Quick Comparison

Indexes are crucial for accelerating database queries, and enhancing the performance of your PostgreSQL applications. However, not all indexes function the same way. Composite and partial indexes are two common types, each with distinct purposes and effects on performance. In this blog, we'll dive into what composite and partial indexes are, how they operate, and when to use them to achieve the best results for your database.
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A Beginner’s Guide to Sharding PostgreSQL with Citus

PostgreSQL is a powerful and open-source relational database system known for its reliability, flexibility, and advanced features. It handles complex queries, ensures data integrity, and can be extended to meet various needs, making it a popular choice for many applications. However, as your data grows and the number of transactions increases, scaling PostgreSQL can be challenging.
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A Follow up on Key PostgreSQL Configuration Parameters for Enhanced Performance – Part 2

In a previous blog post, we configured an EC2 instance and installed PostgreSQL on it. After the initial setup, we ran pgbench to measure the initial TPS (transactions per second). Then, we tuned PostgreSQL and reran pgbench to see how much we could improve the TPS. To tune PostgreSQL, we adjusted various parameters based on the system's available resources. In this blog, we will identify which of those parameters contributed the most to the performance improvements. We will use the same instance size on AWS EC2 as before, which is t2.large. Here is the list of parameters that we initially tuned...
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