Postgres Monitoring, Database Optimization and more

Efficient Pagination in Django and Postgres

20 July, 2021

You could say most web frameworks take a naive approach to pagination. Using PostgreSQL’s , , and features works fine for the majority of web applications, but if you have tables with a million records or more, performance degrades quickly. Django is an excellent framework for building web applications, but its default pagination method falls into this trap at scale. In this article, I’ll help you understand Django’s pagination limitations and offer three alternative methods that will improve…

PostgreSQL Partitioning in Django

08 July, 2021

Postgres 10 introduced partitioning to improve performance for very large database tables. You will typically start to see the performance benefits with tables of 1 million or more records, but the technical complexity usually doesn’t pay off unless you’re dealing with hundreds of gigabytes of data. Though there are several advantages to partitioning, it requires more tables, which can become cumbersome to work with, especially if you change your data structure in the future. Please note: If you…

Using GeoDjango and PostGIS in Django

24 June, 2021

Spatial data is any geographic data that contains information related to the earth, such as rivers, boundaries, cities, or natural landmarks. It describes the contours, topology, size, and shape of these features. Maps are a common method of visualizing spatial data, which is typically represented in vector or raster form. In this article, I’ll introduce you to spatial data in PostgreSQL and Django. You’ll see how to use PostGIS and GeoDjango to create, store, and manipulate geographic data…

Using Postgres Row-Level Security in Ruby on Rails

25 May, 2021

Securing access to your Postgres database is more important than ever. With applications growing more complex, often times using multiple programming languages and frameworks within the same app, it can be challenging to ensure access to customer data is handled consistently. For example, if you are building a SaaS application where different companies use the application, you don't want users of Company A to see the data of users in Company B by accident. Sure, you could use create a separate…

An early look at Postgres 14: Performance and Monitoring Improvements

21 May, 2021

The first beta release of the upcoming Postgres 14 release was made available yesterday. In this article we'll take a first look at what's in the beta, with an emphasis on one major performance improvement, as well as three monitoring improvements that caught our attention. Before we get started, I wanted to highlight what always strikes me as an important unique aspect of Postgres: Compared to most other open-source database systems, Postgres is not the project of a single company, but rather…

Creating Custom Postgres Data Types in Rails

22 April, 2021

Postgres ships with the most widely used common data types, like integers and text, built in, but it's also flexible enough to allow you to define your own data types if your project demands it. Say you're saving price data and you want to ensure that it’s never negative. You might create a type that you could then use to define columns on multiple tables. Or maybe you have data that makes more sense grouped together, like GPS coordinates. Postgres allows you to create a type to hold that data…

Introducing pg_query 2.0: The easiest way to parse Postgres queries

18 March, 2021

The query parser is a core component of Postgres: the database needs to understand what data you're asking for in order to return the right results. But this functionality is also useful for all sorts of other tools that work with Postgres queries. A few years ago, we released pg_query to support this functionality in a standalone C library. pganalyze uses pg_query to parse and analyze every SQL query that runs on your Postgres database. Our initial motivation was to create pg_query for checking…

Efficient Postgres Full Text Search in Django

24 February, 2021

In this article, we'll take a look at making use of the built-in, natural language based Postgres Full Text Search in Django. Internet users have gotten increasingly discerning when it comes to search. When they type a keyword into your website's search bar, they expect to find logically ranked results, including related matches and misspellings. Because users are used to these sophisticated search systems, developers have to build applications that use more than simple queries. Postgres Full…

Creating Custom Postgres Data Types in Django

15 December, 2020

Postgres allows you to define custom data types when the default types provided don't fit your needs. There are many situations where these custom data types come in handy. For example, if you have multiple columns in several tables that should be an between 0 and 255, you could use a custom data type so that you only have to define the constraints once. Or, if you have complex data - like metadata about a file - and you want to save it to a single column instead of spreading it across several…

PostGIS vs. Geocoder in Rails

01 October, 2020

This article sets out to compare PostGIS in Rails with Geocoder and to highlight a couple of the areas where you'll want to (or need to) reach for one over the other. I will also present some of the terminology and libraries that I found along the way of working on this project and article as I set out to understand PostGIS better and how it is integrated with Rails. If you are interested in learning how to work with geospatial data with PostGIS in Django I recommend having a look at our blog…

Lessons Learned from Running Postgres 13: Better Performance, Monitoring & More

21 September, 2020

Postgres 13 is almost here. It's been in beta since May, and the general availability release is coming any day. We've been following Postgres 13 closely here at pganalyze, and have been running the beta in one of our staging environments for several months now. There are no big new features in Postgres 13, but there are a lot of small but important incremental improvements. Let's take a look. Performance Smaller Indexes with B-Tree Deduplication Extended Statistics Improvements in Postgres 1…

Using Postgres Row-Level Security in Python and Django

13 August, 2020

Postgres introduced row-level security in 2016 to give database administrators a way to limit the rows a user can access, adding an extra layer of data protection. What's nice about RLS is that if a user tries to select or alter a row they don't have access to, their query will return 0 rows, rather than throwing a permissions error. This way, a user can use , and they will only receive the rows they have access to with no knowledge of rows they don't. Most examples of RLS limit row access by…

Using Postgres JSONB Fields in Django

30 July, 2020

I remember the first time I built user preferences into an app. At first, users just needed to be able to opt in or out of our weekly emails. "No big deal," I thought, "I'll just add a new field on the Users table." For a while, that was fine. A few weeks later, my boss asked me if we could let users opt into push notifications. Fine, that's just one more column on the database. Can't hurt, right? You probably see where this is going. Within months, my user table had 40 columns, and while…

Building SVG Components in React

09 July, 2020

React is well known as a great tool for building complex applications from HTML and CSS, but that same approach can also be used with SVG to build sophisticated custom UI elements. In this article, we'll give a brief overview of SVG, when to use it (and when not to), and how to use it effectively in a React application. We'll also briefly touch on how to integrate with d3 (which comes in very useful when working with SVG). We relied heavily on SVG to build the charting updates we launched…

Advanced Active Record: Using Subqueries in Rails

24 June, 2020

Active Record provides a great balance between the ability to perform simple queries simply, and also the ability to access the raw SQL sometimes required to get our jobs done. In this article, we will see a number of real-life examples of business needs that may arise at our jobs. They will come in the form of a request for data from someone else at the company, where we will first translate the request into SQL, and then into the Rails code necessary to find those records. We will be covering…

Introducing New Charts & Date Picker in pganalyze

29 April, 2020

Clear and flexible presentation of data is the bread and butter of a monitoring service. A good one will display the right data, but a great one can guide you toward meaningful insights. Visual representation of data in a clear and concise way can help you make decisions quickly. Today we're releasing multiple updates to pganalyze that will help you get to insights more effectively, and keep your database running smoothly. Date range selection as a first-class concept Consistent charts across…

Full Text Search in Milliseconds with Rails and PostgreSQL

16 April, 2020

Imagine the following scenario: You have a database full of job titles and descriptions, and you’re trying to find the best match. Typically you’d start by using an ILIKE expression, but this requires the search phrase to be an exact match. Then you might use trigrams, allowing spelling mistakes and inexact matches based on word similarity, but this makes it difficult to search using multiple words. What you really want to use is Full Text Search, providing the benefits of ILIKE and trigrams…

Effectively Using Materialized Views in Ruby on Rails

16 January, 2020

It's every developer's nightmare: SQL queries that get large and unwieldy. This can happen fairly quickly with the addition of multiple joins, a subquery and some complicated filtering logic. I have personally seen queries grow to nearly one hundred lines long in both the financial services and health industries. Luckily Postgres provides two ways to encapsulate large queries: Views and Materialized Views. In this article, we will cover in detail how to utilize both views and materialized views…

Introducing Automated Postgres EXPLAIN Visualization & Insights

16 December, 2019

Today, we’re excited to introduce you to the next evolution of pganalyze. We updated our logo and overall brand, worked on our documentation to help you understand Postgres and its internals better and, most importantly, we’re proud to announce a new key feature on our platform: Automated EXPLAIN Visualization & Insights. Automatic Collection of Query Plans Automatic Visualization of Postgres EXPLAIN Plans pganalyze EXPLAIN Insights The new pganalyze brand Offering this functionality to you is…

Similarity in Postgres and Rails using Trigrams

19 November, 2019

You typed "postgras", did you mean "postgres"? Use the best tool for the job. It seems like solid advice, but there's something to say about keeping things simple. There is a training and maintenance cost that comes with supporting an ever growing number of tools. It may be better advice to use an existing tool that works well, although not perfect, until it hurts. It all depends on your specific case. Postgres is an amazing relational database, and it supports more features than you might…

Efficient GraphQL queries in Ruby on Rails & Postgres

24 September, 2019

GraphQL puts the user in control of their own destiny. Yes, they are confined to your schema, but beyond that they can access the data in any which way. Will they ask only for the "events", or also for the "category" of each event? We don't really know! In REST based APIs we know ahead of time what will be rendered, and can plan ahead by generating the required data efficiently, often by eager-loading the data we know we'll need. In this article, we will discuss what N+1 queries are, how they…

Postgres Connection Tracing, Wait Event Analysis & Vacuum Monitoring go into GA on pganalyze

14 April, 2019

We’re excited to announce the general availability of three new pganalyze features: Connection Tracing, Wait Event Analysis, as well as Vacuum Monitoring. These features have been developed based on the feedback of hundreds of customers monitoring their production Postgres databases using pganalyze. Thanks so much for consistently taking the time to provide us with valuable information on how you’d like to see pganalyze evolve! Postgres Connection Tracing & Wait Event Analysis One of the most…

New in Postgres 11: Monitoring JIT performance, Auto Prewarm & Stored Procedures

04 October, 2018

Everyone’s favorite database, PostgreSQL, has a new release coming out soon: Postgres 11 In this post we take a look at some of the new features that are part of the release, and in particular review the things you may need to monitor, or can utilize to increase your application and query performance. Just-In-Time compilation (JIT) in Postgres 11 Just-In-Time compilation (JIT) for query execution was added in Postgres 11. It's not going to be enabled for queries by default, similar to parallel…

Postgres Log Monitoring with pganalyze: Introducing Log Insights 2.0

24 July, 2018

TLDR: We recently released substantial improvements to our Log Insights feature, including up to 30 day history, support for Heroku Postgres, as well as support for monitoring the log files of PostgreSQL servers running on-premise. How pganalyze parses Postgres log files Its now been a bit over a year since we first released the log monitoring functionality in pganalyze, and we would like to share a major update with you today. Before diving in, a quick review how the pganalyze collector works…

Postgres Log Monitoring 101: Deadlocks, Checkpoint Tuning & Blocked Queries

12 February, 2018

Those of us who operate production PostgreSQL databases have many jobs to do - and often there isn't enough time to take a regular look at the Postgres log files. However, often times those logs contain critical details on how new application code is affecting the database due to locking issues, or how certain configuration parameters cause the database to produce I/O spikes. This post highlights three common performance problems you can find by looking at, and automatically filtering your…

Visualizing & Tuning Postgres Autovacuum

28 November, 2017

In this post we'll take a deep dive into one of the mysteries of PostgreSQL: VACUUM and autovacuum. The Postgres autovacuum logic can be tricky to understand and tune - it has many moving parts, and is hard to understand, in particular for application developers who don't spend all day looking at database documentation. But luckily there are recent improvements in Postgres, in particular the addition of pg_stat_progress_vacuum in Postgres 9.6, that make understanding autovacuum and VACUUM…

Whats New in Postgres 10: Monitoring Improvements

04 October, 2017

Postgres 10 has been stamped on Monday, and will most likely be released this week, so this seems like a good time to review what this new release brings in terms of Monitoring functionality built into the database. In this post you'll see a few things that we find exciting about the new release, as well as some tips on what to adjust, whether you use a hosted Postgres monitoring tool like pganalyze, or if you've written your own scripts. New "pg_monitor" Monitoring Role Most users of Postgres…

Introducing Log Insights: Realtime Analysis of Postgres Logs

07 June, 2017

After significant development effort, we're excited to introduce you to a new part of pganalyze that we believe every production Postgres database needs: pganalyze Log Insights UPDATE: We released pganalyze Log Insights 2.0 - read more about it in our article: Postgres Log Monitoring with pganalyze: Introducing Log Insights. In the past you used generic log management systems and setup your own filtering and altering rules, which required a lot of manual effort, as well as knowledge of all…

Monitoring PostgreSQL 9.5 & Improved Weekly Reports

06 July, 2015

Last week the first official alpha version of PostgreSQL 9.5 was released. Whilst the stable release is still 2-3 months away, now is a good time to review what is upcoming, and which changes and improvements we can expect. Here is an overview of the most important changes for monitoring tools: pg_stat_statements gets new columns min_time, max_time, mean_time & stddev_time - making it much easier to identify outliers in the query statistics New pg_stat_ssl view that shows active SSL connections…

Introducing pg_query: Parse PostgreSQL queries in Ruby

17 June, 2014

In this article we'll take a look at the new pg_query Ruby library. pg_query is a Ruby library I wrote to help you parse SQL queries and work with the PostgreSQL parse tree. We use this extension inside pganalyze to provide contextual information for each query and find columns which might need an index. At the end of this article you'll also find monitor.rb - a ready-to-use example that filters pg_stat_statements output and restricts it to only show a specific table. Existing Solutions to Parse…

Announcing The All-New Database Check-Up

20 March, 2014

We’ve just launched our new version of Database Check-Up - allowing you to see more quickly what could be relevant to look at in your database. In addition we’ve also revamped the detail pages of queries, tables, indices and config settings to match the new style: Improved Check-Up: Config Settings When working with other people's PostgreSQL databases, we’ve seen a lot of things, from fsync=off (which you really only want if you don’t care about your data or have no writes) to simple…