If you are already familiar with other SQL databases but new to PostgreSQL, then this article is perfect for you. It will help you understand the nuances and get started with PostgreSQL.
Note: Most comparisons in this article are targeted towards MySQL since it is the closest open source database that PostgreSQL can be compared against.
Analyzing Scans in PostgreSQL
Introduction and Data Setup
Before we dive in, it is vital to understand the basic elementary blocks of PostgreSQL query plans. This has been covered in a separate blog post, and I highly encourage readers to go through it first.
There are several node types in PostgreSQL query plans,
Probing Text Data Using PostgreSQL Full-Text Search
Introduction
Recap
In the previous article, we saw how we could use fuzzy search in PostgreSQL. This article is more about using the power of full-text indexes to search through large text data. This is different from any other PostgreSQL indexes, which work either with alphanumeric or smaller textual content.
Dataset Preparation
To understand how full-text search works, we are going to utilize the same data set we saw in the PostgreSQL Fuzzy Search blog -
Data Replication for DBMS Using the Commit Log
Introduction
In this article, we will see how developers can break down information silos for their teams and business by replicating data across multiple systems. First, we will review why developers will replicate data and considerations for the cloud. Second, we will prepare for war with the replicators. Then we will examine the architecture of Postgres and MySQL and how their commit logs enable us to make exact copies of the data. Finally, we will connect Debezium to Postgres for a complete data replication solution.
Introduction to Data Replication
Data replication is the process of moving data between different database systems for various business use cases. In a typical SaaS (Software As A Service) application, data is stored in an operational database such as MySQL, PostgreSQL, Oracle, etc. There are other database systems such as data warehouses and search systems built for specialized use cases. Moving data between these systems is known as data replication.
Use MySQL Window Functions to Get More Out of Your Data
Window Functions in MySQL
Window functions are an advanced feature offered by MySQL to improve the execution performance of queries. These functions act on a group of rows related to the targeted row called window frame. Unlike a GROUP BY clause, Window functions do not collapse the rows to a single row — preserving the details of each row instead. This new approach to querying data is invaluable in data analytics and business intelligence.
Window Functions vs. Aggregate Functions
Aggregate functions are used to return a single scalar value from a set of rows. Some prominent aggregate functions available in MySQL are SUM, MIN, MAX, AVG, and COUNT. We can use these functions combined with the GROUP BY clause to get an aggregated value.
Does Product-Led Growth Produce Better Companies?
After serving two years in the Peace Corps, I knew I wanted to join a startup, but I immediately faced a dilemma — there are too many startups from which to choose. Some early teams, like Arctype, do distinguish themselves through their overwhelming focus on product experience, which is why today, I'm going to use SQL to analyze the performance of public SaaS companies that have historically shared this focus. Through this analysis, I hope to answer the following question: are these so-called 'product-led growth' companies truly better? Did I make the right long-term financial decision in joining Arctype?
According to product adoption platform Pendo, product-led growth (PLG) relies upon the product itself — its features, performance, and virality — to do much of the 'selling.' At Arctype, we are following this strategy by focusing on the speed and developer experience of both our query editor and SQL IDE to convert users.