Why Data Engineers use PostgreSQL for Large, Data-driven Applications

Key Takeaways:

1. PostgreSQL is an enterprise-class Open Source Database Management System
2. It is scalable, flexible, and extensible making it the DB of choice to build next-generation, large scale applications
3. Thanks to a wonderful developer community of PostgreSQL experts, new modules are added to continuously improve its performance

PostgreSQL was recognized by DB-Engines as the DBMS for the year 2020, the only DBMS to win it for the third time. Its stability and feature sets have made it very popular among data engineers, and in recent releases, there have been many improvements under the hood especially in its performance and efficiency. As a result, it has benefited DevOps teams tremendously and its popularity scores have gone up from 167 seven years ago to 552 in 2020.

Why Reddit Uses PostgreSQL

Reddit, a social news website, has more than 174 million registered users who are constantly exchanging opinions and knowledge. It is among the 25 most popular websites in the world, as per Alexa Rankings.

PostgreSQL helps to store data for most objects such as links, accounts, comments, and subreddits using the ThingDB model. A more traditional relational database based on PostgreSQL helps Reddit with maintaining and analysing traffic statistics and information related to subscriptions, transactions, and ad sales.

Some of the features of PostgreSQL that makes it popular amongst businesses such as IKEA, Reddit, Skype, and more are its:

• Proven architecture
• Reliability
• Data integrity
• Robust feature set
• Extensibility

These are further enhanced by a dedicated open-source community that enables the delivery of performance and innovative solutions. The RDBMS works on any operating system that has been ACID-compliant since 2001 and includes add-ons such as PostGIS geospatial database extender.

Started as part of the POSTGRES project at the University of California at Berkeley in 1986, this powerful, open-source object-relational database system enables storing and scaling even complicated data workloads by using and extending the SQL language integrated with many features that are being constantly added.

Read about other advanced tools recommended by Merit’s data engineering experts for powering and optimising your BI Stack.

Key Benefits of PostgreSQL

Some of the features that make PostgreSQL a popular RDBMS include:

1. Open Source: Being Open Source, it is free. But that’s not why it’s popular. Its enterprise-class performance and functions open up several development possibilities for applications, helps administrators with protecting data integrity and building fault-tolerant environments, and it helps improve the management of data regardless of the size of the dataset.

2. Community Support: A very active community has contributed to the growth of PostgreSQL by contributing modules and facilitating interactions between members in resolving bugs.

3. Function and Querying: PostgreSQL uses SQL functions called ‘Store Procedure’ in the server environment and supports languages such as PL/pgSQL, PL/Python, PL/Perl, C/C++, and PL/R. PostgreSQL conforms to and supports SQL standards with some variations to syntax and function, and with every release, it goes closer to SQL:2016 Core conformance. For non-relational querying, it supports JSON.

4. Compliance: A highly fault-tolerant database with its write-ahead logging feature, PostgreSQL is ACID (Atomicity, Consistency, Isolation, Durability) compliant. It supports foreign keys and allows joining, viewing, triggering, and storing procedures in different languages. Apart from including many SQL:2008 data types such as integer, Boolean, numeric, CHAR, VARCHAR, timestamp, date, and interval, binary large objects such as pictures, sounds, or video can also be stored. Some of its other features include Multi-Version Concurrency Control (MVCC), point in time recovery, tablespaces, asynchronous replication, nested transactions, online/hot backups, a refined query planner/optimizer, and granular access controls.

5. Diverse Indexing Techniques: B+ tree index techniques, GIN (Generalized Inverted Index), and GiST(Generalized Search Tree) are some of the many indexing techniques available in PostgreSQL. Its general purpose OLTP database is used by large enterprises as well as startups as the primary data store for supporting internet-scale applications, products, and solutions. The geospatial database enables storing geographic objects to facilitate location-based services and geographic information systems (GIS). To link PostgreSQL with other data stores including NoSQL ones, Foreign Data Wrappers, and JSON support make it a federated hub for polyglot database systems.

6. Flexible Full-text Search: PostgreSQL also facilitates execution of vector operation and string search for full-text search to look for strings. It is also highly scalable, be it storing a high volume of data the number of concurrent users it can manage at a time.

7. Diverse Kinds of Replication: Some of the many replication methods supported by PostgreSQL include Streaming Replication, cascading, and Slony-I.

8. Diversified Extension Functions: Apart from techniques such as PostGIS for geographic data stores, PostgreSQL includes many other extensions for functions such as Key-Value Store and DBLink. This provides you with the flexibility to define your own data types, create custom functions, and write code using different programming languages without having to recompile your database.

Use Cases of PostgreSQL

PostgreSQL finds use across industries and functions, including:

Financial Industry: Being ACID compliant, PostgreSQL is ideal for the financial industry for OLTP (Online Transaction Processing). It can be used to perform database analytics and can be integrated with mathematical software such as Matlab and R.

GeoData: The standard-compliant GIS extension, PostGIS, enables processing of geometric data in multiple formats. Handling Geodata is further made easy with the use of both QGIS or GeoServer.

Manufacturing: PostgreSQL can help manufacturers speed up their business processes, reduce operational costs, and optimize supply chain performance.

Website Management: PostgreSQL’s replication capability makes it a scalable solution providing as many database servers as required. This makes it ideal for websites that deal with several hundred or thousands of requests per second at a time. It works well with modern web frameworks such as Django, Node.js, PHP, and Hibernate.

Scientific Research: Scientific research and projects require terabytes of data, which needs to be handled efficiently. The SQL engine and the analytical capabilities of PostgreSQL help to manage the vast amounts of data easily and draw insights quickly.

About Merit Group

At Merit Group, we work with some of the world’s leading B2B intelligence companies like Wilmington, Dow Jones, Glenigan, and Haymarket. Our data and engineering teams work closely with our clients to build data products and business intelligence tools. Our work directly impacts business growth by helping our clients to identify high-growth opportunities.

Our specific services include high-volume data collection, data transformation using AI and ML, web watching, and customized application development.

Our team also brings to the table deep expertise in building real-time data streaming and data processing applications. Our expertise in data engineering is especially useful in this context. Our data engineering team brings to fore specific expertise in a wide range of data tools including Kafka, Python, PostgreSQL, MongoDB, Apache Spark, Snowflake, Redshift, Athena, Looker, and BigQuery.

If you’d like to learn more about our service offerings or speak to a Kafka expert, please contact us here: https://www.meritdata-tech.com/contact-us/