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Drupal with PostgreSQL Developer Salary in 2024

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Total:
22
Median Salary Expectations:
$66,054
Proposals:
0.5

How statistics are calculated

We count how many offers each candidate received and for what salary. For example, if a Drupal with PostgreSQL with a salary of $4,500 received 10 offers, then we would count him 10 times. If there were no offers, then he would not get into the statistics either.

The graph column is the total number of offers. This is not the number of vacancies, but an indicator of the level of demand. The more offers there are, the more companies try to hire such a specialist. 5k+ includes candidates with salaries >= $5,000 and < $5,500.

Median Salary Expectation – the weighted average of the market offer in the selected specialization, that is, the most frequent job offers for the selected specialization received by candidates. We do not count accepted or rejected offers.

Where is PostgreSQL used?


The Hidden Prowess of PostgreSQL



  • Under the hood of your favorite Insta-food pics, PostgreSQL is the chef curating and serving your feed without a hiccup.

  • Got a retail therapy bot? Thank Postgres for not buying 12 pairs of socks when you just wanted one.

  • In the gaming realm, Postgres is the stealthy NPC keeping score while you're out there claiming virtual glory.

  • Imagine the world's biggest library with a grumpy librarian; that's PostgreSQL in charge of healthcare records, except it never shushes you.

PostgreSQL Alternatives


MySQL



MySQL is an open-source relational database management system. It's known for its ease of use and speed, and it's often used for web applications.



  • Widely used and supported

  • Flexible and easy to set up

  • Performs well in web applications

  • Limited functionalities compared to PostgreSQL

  • Less advanced security features

  • Performance can degrade with complex queries



-- MySQL
SELECT * FROM users WHERE age > 25;

-- PostgreSQL
SELECT * FROM users WHERE age > 25;


MongoDB



MongoDB is a NoSQL database that stores data in JSON-like documents. It excels in applications that need quick iteration and flexible data models.



  • Highly scalable

  • Flexible document schemas

  • Agile and developer-friendly

  • Transactions are less robust than SQL

  • Joins and complex queries can be challenging

  • Data consistency can be an issue



// MongoDB
db.users.find({ age: { $gt: 25 } });

// PostgreSQL
SELECT * FROM users WHERE age > 25;


SQLite



SQLite is a self-contained, serverless, zero-configuration, transactional SQL database engine. It's perfect for mobile and lightweight applications.



  • Lightweight and self-contained

  • Zero-configuration necessary

  • Good for embedded applications

  • Not suited for high concurrency

  • Lacks advanced features

  • Write operations are serialized



-- SQLite
SELECT * FROM users WHERE age > 25;

-- PostgreSQL
SELECT * FROM users WHERE age > 25;

Quick Facts about PostgreSQL


Back in Time: PostgreSQL’s Baby Steps


Imagine it’s 1986, and the computer world is buzzing with neon leg warmers and side-ponytails. Michael Stonebraker, a dude with a vision from the University of California at Berkeley, kicks off the PostgreSQL journey with a project named POSTGRES. This project was meant to evolve the groundbreaking Ingres database into something even cooler, like trading in a Walkman for an iPod.



From SQL Whispers to Roars


By 1995, POSTGRES was teaching itself a new trick: speaking SQL. Yes, that's like learning French in Paris! The addition of SQL transformed POSTGRES into PostgreSQL, giving it a language everyone at the data party understands. It's like going from using Morse code to hosting a slick podcast.



Shapeshifting Through Versions: The PostgreSQL Chameleon


PostgreSQL has been through more costume changes than a pop star. From the vintage 6.0 release in 1997, which was like the 8-track tape of databases, to the fresh-as-avocado-toast PostgreSQL 14 in 2021, PostgreSQL is the Madonna of databases. With each release, it struts out new features like data types faster than a quick-change act!




// Let's say it's the '90s and you're adding 'Hello World' to your database:
INSERT INTO table_of_cool (message) VALUES ('Hello World');

What is the difference between Junior, Middle, Senior and Expert PostgreSQL developer?


































Seniority NameYears of ExperienceAverage Salary (USD/year)Responsibilities & Activities
Junior PostgreSQL Developer0-250,000-70,000

  • Writing basic SQL queries.

  • Assisting with database maintenance.

  • Learning and following best practices.

  • Performing simple database optimizations.


Middle PostgreSQL Developer2-570,000-100,000

  • Developing more complex SQL queries.

  • Designing and implementing table schemas.

  • Writing stored procedures and functions.

  • Optimizing queries for performance.


Senior PostgreSQL Developer5-10100,000-130,000

  • Architecting database structure for large-scale applications.

  • Leading database optimization and scaling efforts.

  • Conducting code and design reviews.

  • Mentoring junior developers.


Expert/Team Lead PostgreSQL Developer10+130,000+

  • Setting strategic direction for database development.

  • Overseeing multiple projects and teams.

  • Managing high availability and disaster recovery plans.

  • Representing the database team in cross-departmental decisions.



Top 10 PostgreSQL Related Tech




  1. SQL Prowess: "Speak the 'Postgres' Lingo"


    Every PostgreSQL developer must be fluent in the native tongue of databases: SQL (Structured Query Language). It's like the Esperanto for data manipulation and retrieval – a must-have in your polyglot programming utility belt. You ought to know how to craft queries that can summon data like magical incantations – from simple SELECT statements to complex JOIN operations capable of bending relations to your will.



    SELECT name, job_title FROM wizards WHERE wand_power > 9000;



  2. PL/pgSQL: "Postgres' Secret Spellbook"


    PL/pgSQL stands for Procedural Language/PostgreSQL SQL, the go-to tool for enchanting PostgreSQL with business logic directly in the database through user-defined functions and stored procedures. Think of it as writing little data-manipulating wizards locked up in your database, ready to perform complex tasks on your command.



    CREATE FUNCTION raise_hp(target_id INT, hp_boost INT) RETURNS VOID AS $$
    BEGIN
    UPDATE adventurers SET hp = hp + hp_boost WHERE id = target_id;
    END;
    $$ LANGUAGE plpgsql;



  3. pgAdmin: "The Crystal Ball of PostgreSQL"


    pgAdmin is like the trusty sidekick for every database sorcerer, a graphical interface to gaze into the depths of your PostgreSQL databases. Through this mystical pane, you can poke around your data, run spells...err...queries, and maintain the health of your database realms without whispering a single command line incantation.




  4. PostGIS: "The Cartographer's Tool"


    For those who need to navigate the mystical lands of geospatial data, PostGIS is the compass that turns PostgreSQL into a spatial database with superpowers. It allows you to conjure up location-based queries and build maps that can reveal hidden patterns like a treasure map x-marks-the-spot.




  5. pgBouncer: "The Bouncer at the Data Tavern"


    pgBouncer stands guard at the entrance to your database, managing the flow of client connections like a burly doorman at a club. It maintains a pool of connections so your database doesn't get trampled by overzealous application servers trying to party all at once.




  6. pgBackRest: "The Keeper of the Scrolls"


    No quest is without risk, and losing your data is akin to letting the evil lord win. pgBackRest is your guardian, ensuring you can always resurrect your data kingdom with backup and restore abilities so powerful they feel like time travel.




  7. Patroni: "The Database Watchtower"


    Patroni stands vigilant, ensuring your PostgreSQL deployment's high availability. It's like having a wise old wizard perched atop the tallest tower, ready to cast failover spells and switch masters like a pro if the current one kicks the cauldron.




  8. Logical Replication: "The Copycat Charm"


    Logical replication allows for copying selected data from one database to another – think of it as creating a clone army of your data. This selective replication is like having doppelgangers for your data that can take up arms in another castle if the fort is about to fall.




  9. PEM (PostgreSQL Enterprise Manager): "The Overseer's Gaze"


    The PostgreSQL Enterprise Manager is like the Eye of Sauron for your databases (but in a less malevolent way). It provides a bird's-eye view of your database landscape, monitoring performance, and alerting you to potential disturbances in the force…err…performance metrics.




  10. Python and psycopg2: "The Alchemist's Mix"


    Mixing Python with psycopg2 is like the alchemy of database interaction. Python's versatility combined with psycopg2's PostgreSQL-specific features let you transmute your queries and data into golden applications with ease.



    import psycopg2

    conn = psycopg2.connect("dbname=spellbook user=magician")
    cur = conn.cursor()
    cur.execute("SELECT * FROM potions WHERE effectiveness > 90")
    potent_potions = cur.fetchall()


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