There is a high demand for professionals with PostgreSQL expertise due to its widespread adoption in various industries. If you’re aiming for a PostgreSQL career, being prepared with the below-listed PostgreSQL interview questions and answers can help you demonstrate your expertise and increase your chances of securing a job. The list comprises basic to advanced-level PostgreSQL questions, along with their well-researched answers.
PostgreSQL is a relational, open-source, and lightweight database. Due to its proven architecture, data integrity, reliability, and integration with programming languages like R and Python, PostgreSQL is highly accepted by the industry, with enterprises of all sizes using it. Big tech organizations like Cisco and Apple are using PostgreSQL in the back-end applications.
Thus, due to its huge popularity, there will be massive job opportunities in PostgreSQL and you can build a promising career. To help you in the interview process, we have curated the most common PostgreSQL interview questions with answers for all experience levels.
Let’s go through important PostgreSQL Interview Questions and Answers at various expertise levels.
PostgreSQL is the freeware object-relational database management called ORDBMS. It is also called Postgres. It is one of the most popular and widely utilized Object-Relational Database Management Systems. It is a strong database management system that offers substantial and additional power by integrating fundamental concepts so that users can extend the database without any problem.
If you want to enrich your career and become a professional in PostgreSQL, then enrol in "PostgreSQL Online Training". This course will help you to achieve excellence in this domain. |
PostgreSQL enables you to
PostgreSQL utilises the “INSERT INTO” statement for adding data to your SQL table.
PostgreSQL provides the following methods to create a new database
We can delete the database by using any one of the below options:
Related article: Comparison Between MongoDB and PostgreSQL |
A database schema includes the visual and logical configuration of the complete relational database. In the PostgreSQL, a schema contains tables with views, datatypes, indexes, constraints, functions, and sequences.
A schema contains tables along with data types, views, indexes, operators, sequences, and functions.
Joins are used for combining and retrieving the records from two or more tables. PostgreSQL utilizes SQL joins for performing these types of operations.
A group of conditions defining the kind of data that acts as input to every column of the table. Constraints will be used for assuring the data integrity in the table and avoid unnecessary actions.
The PostgreSQL operators include - Arithmetic operators, Comparison operators, Logical operators, and Bitwise operators.
A Primary Key enables only a unique value and non-null values, whereas a foreign key offers shared keys between two or more tables.
PostgreSQL offers the following constraints:
The view depicts the query result to one or multiple inherent tables. Views are used to simplify difficult queries as these queries are defined once in the view and can be directly queried.
In Database, Normalization is a mechanism through which we can create or modify the databases and tables for handling the inefficiencies related to data storage, querying processes, or data modification. In other terms, normalization includes multiple steps for reducing data complexity and redundancy.
Triggers, also called as the callback function, is the specification that a database must automatically implement a specific function whenever a particular kind of operation is carried out. We can define the triggers for executing either before or after the INSERT, UPDATE, or DELETE operation, either once per SQL statement or once per the modified row. If the trigger event happens, the trigger’s function is invoked at the proper time for handling the event. Triggers allow you to ensure the data integrity while modifying the database.
By executing the following query, we can select the first seven rows in a table:
SELECT * from employees LIMIT 7;
PostgreSQL utilizes the client-server model to receive the request from the end user, process it, and return it to the client. It is a process per-user client-server model in which a new process will be started for every client connection request, and the PostgreSQL server process processes the client request. The PostgreSQL server process will perform all the operations in support of the client process.
1. Postmaster Supervisor Process
Postmaster serves as the supervisor in PostgreSQL architecture, and it is the first process that will start after PostgreSQL starts. It serves as the Listener and is accountable for authorizing and authenticating the incoming request from client and allocating a new method called postgres for every connection. It also monitors the process and starts if it is dead.
2. Shared Memory Segments
Shared Memory Segments are buffer caches in the memory that are reserved for transactions and maintenance activities. There are various shared memory segments assigned for performing a different operation.
3. Background process of PostgreSQL
The background processes are the crucial components of the PostgreSQL database. These processes are used for maintaining the consistency between the disk and memory, and because of this, PostgreSQL will work properly. Every PostgreSQL background process will play its role. The following is the list of background processes:
The Physical Files are used for storing the actual data in the form of the data files, the Archive log information, the server log details in log files, the changed blocks in the WAL files, etc. The data in the files are stored permanently and are utilized for their corresponding operation.
The following are the physical files in PostgreSQL:
In PostgreSQL, the primary key is the column or group of columns uniquely identifying every row in the table. It assures the integrity and uniqueness of the data in the table. The primary key constraint applies the rules below:
For defining the primary key in the PostgreSQL, we can utilize the “PRIMARY KEY” constraint while creating or altering the table for adding the constraint. We can define only one primary key per one table.
For installing PostgreSQL, we have to follow the below steps:
Related article: How to Install PostgreSQL? |
There are several benefits of using PostgreSQL
In PostgreSQL, a Foreign Key is a column or group of columns that sets up the link between two tables. It depicts the relationship between the referenced table(parent table) and the referencing table(child table). The foreign key assures the referential integrity, applying the rules below:
For defining the foreign key in PostgreSQL, we can utilize the foreign key constraint while altering the table or creating the table for adding the constraint. The foreign key columns in referencing table should have same data type as primary key columns in referenced table.
Yes, we can run PostgreSQL on the most famous cloud providers like AWS, Google Cloud, and Azure.
Multi-Version Concurrency Control is the advanced technique of PostgreSQL. It improves the database performance in the multi-user scenarios. This indicates that when we query the database, every transaction views a snapshot of the database since it was some time ago, irrespective of the present state of inherent data. This secures the transaction from seeing the inconsistent data that concurrent transaction updates on the similar data rows can induce.
Creating a backup of your database in PostgreSQL is simple. There are several methods for performing a backup in PostgreSQL like On-line backup, SQL dump, and File system-level backup.
Partitioning enables you to divide the table into smaller, more manageable partitions, which convert into improved query performance. It’s specifically ideal while handling massive tables.
There are three primary commands for controlling the transactions in the PostgreSQL
The pgAdmin in PostgreSQL is a data administration tool. It serves the purpose of retrieving, developing, testing, and maintaining databases.
PL/Python is a procedural language to which PostgreSQL provides support.
The following are the different strategies to enhance the query performance:
In PostgreSQL, to handle errors, we have the following ways:
The database callback functions are called PostgreSQL Triggers. When a specified database event occurs, the PostgreSQL Triggers are performed or invoked automatically.
Cluster index sorts table data rows based on their key values.
Some of these benefits include consistency, compactness, validation, and performance.
To update statistics in PostgreSQL, we need to use a special function called a vacuum.
Though the DROP TABLE command has the ability to delete complete data from an existing table, the disadvantage with it is - it removes the complete table structure from the database. Due to this, we need to re-create a table to store data.
There are two primary ways for removing the rows in the table: the TRUNCATE command and the DELETE command. The former is developed to remove rows more wisely and needs a complete scan of the tables. The latter rapidly all the rows and empty disks without table scan. Thus, the TRUNCATE command is the most ideal one.
In PostgreSQL, Security is addressed on various levels:
For deleting a table in the PostgreSQL, use “DROP TABLE” command, followed by the name of the table. For deleting any other object related to it, we have to add “CASCADE” command.
PostgreSQL logs are a valuable resource to troubleshoot the problems, audit the database activity, and track performance. PostgreSQL contains a broad variety of logs, like error logs. These logs can allow you to identify the queries and statements that cause errors during the execution.
The “EXPLAIN” command displays the execution plan of the SQL statement. This contains the way the tables referenced in our statement will be processed, the inherent algorithms used for difficult operations, like joins and the estimated execution time.
Besides the estimated time, if you have to know the actual time needed, you can add the “ANALYZE” command, and the statement will be executed, not planned. The “EXECUTE ANALYZE” command is used for identifying the problems in the difficult queries so that we can rewrite them for enhancing the query performance.
The “pg_dump” method enables you to create the text file with a group of SQL commands that, when we run in the PostgreSQL server, will recreate database in the same state since it was at the time of dump.
In PostgreSQL, the maximum size for a table is 32 TB.
In PostgreSQL, we will use the “CREATE INDEX” statement for creating the index. Here is an example:
CREATE INDEX Emp_Index ON Employee(Emp_ID, Emp_Name, Emp_Salary);
The above statement will create index on “Employee” table.
In PostgreSQL, Composite Type enables you to define the custom data structures that can store multiple values of the different data types. It allows you to create the user-defined types made up of the available data types. Composite types are helpful when grouping the associated data elements into one entity. To define the Composite type, we can utilize the “CREATE TYPE” statement. For example:
CREATE TYPE country_type as(state VARCHAR, city VARCHAR, District VARCHAR);
In the above example, the country_type composite type includes three fields: state, city, and district.
We can delete complete data from an existing table using the PostgreSQL TRUNCATE TABLE command.
The properties of a transaction in PostgreSQL include Atomicity, Consistency, Isolation, and Durability. These are referred to by the acronym, namely ACID.
The CTIDs field identifies the specific physical rows in a table according to their block and offsets positions in that table.
The commands used to control transactions in PostgreSQL are BEGIN TRANSACTION, COMMIT, and ROLLBACK.
PostgreSQL manages the concurrent updates using its MVCC(Multi-Version Concurrency Control) mechanism. It enables multiple transactions to use the same data simultaneously without causing conflicts or blocking each other.
When two transactions try to modify same data concurrently, PostgreSQL assures isolation by creating separate data copies for every transaction. In this way, every transaction sees the consistent snapshot of data as it showed up at the starting of transaction. PostgreSQL offers different isolation levels and locking mechanisms for handling concurrent updates if any conflicts happen.
Developers will select proper transaction isolation levels like REPEATABLE READ, READ COMMITTED, and SERIALIZABLE per their application’s needs and exchanges between data consistency and concurrency.
In PostgreSQL, a materialized view is the database object that stores the results of the query as a physical table. In contrast to regular views, which are virtual and execute inherent queries every time they are used, materialized views are updated and precomputed manually or periodically.
For creating the materialized view, we can utilize the “CREATE MATERIALIZED VIEW” statement, declaring the query that defines the contents of the view. The materialized view is formulated with a query when it is refreshed or created.
They are helpful when you have difficult and resource-intensive queries that are executed regularly. However, their inherent data only changes slowly. By storing and precomputing results, we can achieve major performance enhancements while querying materialized views.
For performing the bulk inserts effectively, we can utilize the “INSERT INTO SELECT…” statement or “COPY” command.
1. INSERT INTO … SELECT statement
INSERT INTO table_name(column1, column2, …) SELECT value1, value2,... UNION ALL SELECT value1, value2, ….
Through the INSERT INTO … SELECT statement, we can insert multiple rows in a single SQL statement. Define the columns and their respective values through the “SELECT” clause, repeating “SELECT” statement for every row we have to insert. This method is used when we have to insert the data generated dynamically or from another table.
2. COPY Command
COPY table_name(column1, column2,...) FROM ‘data_file’ WITH(FORMAT csv);
“COPY” command will read the data from the file given by “data_file” and insert it into specified table. The file must include data in the format that matches the given format. This method is rapid and useful for huge datasets.
A Stored Procedure is pre-compiled, and the stored database object that binds a set of SQL statements. It enables you to carry out difficult operations and implement them as a unit. The advantages of utilizing stored procedures are code reusability, improved security, and enhanced performance.
For creating the stored procedure, we can execute CREATE PROCEDURE or CREATE FUNCTION statements. A stored procedure will have the input and output parameters, control flow logic and local variables through the loops and conditionals. It will also return the result sets through the “OUT” or “RETURN TABLE” parameters.
For creating a view in the PostgreSQL, we have to use the "CREATE VIEW" command. Example:
CREATE VIEW view1 as select * from emp where dept_id = ‘HR’
The above view is created for employees of the 'HR' department in the "emp" table.
The primary difference between CTE and Subquery is their usage and structure.
Both UNION ALL and UNION are used for combining the results of the multiple "SELECT" statements. But, they differ in terms of their result sets and behaviour.
Table Partitioning will allow you to split the large table into small, manageable pieces known as partitions. Every partition stores the subset of the data as per the specified partitioning key. To implement the table partitioning, follow the below steps:
The partitioning feature of PostgreSQL offers automatic routing of data to the proper portions as per the partitioning key, leading to simplified data management and enhanced query performance.
Atomicity property ensures the successful completion of all the operations in a work unit.
Write-ahead logging enhances database reliability by logging changes before any changes or updates are made to the database.
Some of the important data administration tools supported by PostgreSQL are Psql, Pgadmin, and Phppgadmin.
We can store the binary data in PostgreSQL either by using bytes or by using the large object feature.
In a non-clustered index, the index rows order doesn’t match the order in actual data.
It is a location in the disk. In this, PostgreSQL stores the data files, which contain indices and tables, etc.
Yes, there are a few disadvantages. Some of these include the following:
Related article: MySQL Vs PostgreSQL Performance |
In a SQL Statement, a token represents an identifier, keyword, quoted identifier, special character symbol, or constant.
PostgreSQL has excellent support to work with the JSON data. We can store, manipulate, and query the JSON documents through different parameters and functions. For storing the JSON data, we can utilize the JSON and jsonb data types. The jsonb offers the binary storage and provides querying and indexing capabilities.
For querying the JSON data, PostgreSQL offers various functions like jsonb_array_elements , jsonb_extract_path, and jsonb_agg. These functions enable you to extract particular values, navigate through the JSON arrays and objects, and aggregate the JSON data. We can also use operators like -> and → for accessing the JSON values and fields directly in the SQL queries. Moreover, PostgreSQL endorses the indexing on the JSONB columns, enabling effective querying of the JSON data.
In the PostgreSQL, VACCUM is a critical process to handle and reclaim the disk space occupied by outdated or deleted data. It performs two primary tasks:
PostgreSQL endorses several methods to implement replication to assure data redundancy and high availability. The two primary replication methods of PostgreSQL are as follows:
1. Physical Replication: This method includes creating the exact copy of main database by constantly streaming write-ahead logs to multiple standby servers. The standby servers will be used for the read-only queries since failover targets if the primary server becomes unavailable.
Streaming Replication is easy to set up and offers real-time applications with low latency.
2. Logical Replication: Logical Replication will replicate the modifications made to particular databases or tables rather than replicating the complete database cluster. It utilizes the publications, subscriptions, and slots for defining what data must be replicated and where. Logical Replication offers more granularity and flexibility but needs monitoring and configuration.
In PostgreSQL, full-text search allows you to perform advanced the text indexing and searching. It is specifically useful to search massive sets of natural language or unstructured text. PostgreSQL offers the tsquery and tsvector data types for handling the full-text searches. The tsvector type depicts the document's textual content, whereas tsquery type depicts search query.
For performing the full-text search, we have to create the full-text search index on the required column through the "CREATE INDEX" statement with "USING" method. After that, we can use the "@@" operator for matching the search query against indexed column.
In the PostgreSQL, we will perform the data migration using the following steps:
The primary difference between regular and materialized views is how they store and handle the data.
Selection between regular views and materialized views depends on particular use cases and the frequency of the data updates.
For performing logical Replication, we have to follow the below steps:
After that, PostgreSQL will replicate the table or schemas from source database to target database, enabling you to maintain them synchronized.
For implementing the parallel query execution, we can follow the below steps:
By configuring these settings and using the parallel-safe operators. PostgreSQL will parallelise the query execution throughout multiple orders, resulting in quicker query performance.
PostgreSQL supports the following kinds of Indexes:
Every index type will have its benefits and is ideal for various scenarios. The index type selection is based on your data's particular characteristics and requirements.
In PostgreSQL, the pg_stat_activity view offers information about the server's currently running activities. It includes a row for every session linked to database and contains details like username, process ID, application name query being executed, and other statistics.
It is generally used for monitoring the database server, checking idle or blocked connections, identifying long-running queries, and gathering performance-related information. By querying this view, administrators will get insights of current activity and the state of database, enabling them to troubleshoot issues, optimize performance, and handle connections efficiently.
In PostgreSQL, a Recursive query is a kind of query that references its outputs. It enables you to carry out the repetitive operations or traverse graphical or hierarchical-like structures. They are built through the "WITH RECURSIVE" clause, which is also called common table expression(CTE). CTE includes two parts: the anchor member, which serves as the base case and the recursive member, which develops on the result of the previous iteration.
The recursive member will refer to CTE itself, enabling you to query iteratively until a particular condition is satisfied. This recursion will enable you to perform hierarchical queries, traverse the tree structures, and handle the recursive data relationships.
PostgreSQL is considered as the advanced version of SQL. Following are some differences between these PostgreSQL and SQL:
A multi-version model enables multiple versions of the same data to existing parallel, whereas a lock model only enables one version of the data to be available at a time and locks the data while it is edited.
In PostgreSQL, a sequence is the database object that creates a sequence of unique integers that can be utilized as default values for the column or as part of the primary key.
A tablespace is a location or the disk where the data files of particular tables or indexes can be stored, enabling more control of disk utilization and file placement.
For creating and handling the user-defined functions, we can utilize “CREATE FUNCTION” statement. Example:
CREATE FUNCTION function_name(Argument1, Argument2) RETURNS return_type AS $$BEGIN
Function Logic
END
We can replace the function_name with the function name. Declare the return types and argument types as per your requirements. Function logic will be written within the BEGIN and END blocks. For calling the function, we will use the following statement:
SELECT function_name(argument1, argument2);
The pg_stat_replication offers the information on the activity and status of the standby servers in the streaming replication setup. By using this view, we can get the following details:
This view is used to monitor the synchronization and health status of the standby servers and assuring the overall stability of replication setup.
Sharding refers to horizontally partitioning data throughout the multiple shards or servers for distributing the load and scaling the database system. To implement the Sharding, we have to follow the following steps:
In PostgreSQL, Row-level security enables you to limit the access to the rows in the table as per specific policies or conditions. To implement the row-level security, we have to follow the following steps:
After implementing the row-level security, PostgreSQL will automatically apply security policies whenever queries are implemented on the related table.
We can use the following techniques to implement data encryption:
The three phenomena that should be prevented between the concurrent transactions are: 1) Dirty Reads, 2) Lost updates, and 3) Inconsistent Reads.
PostgreSQL | Oracle |
PostgreSQL is an open-source and free object-relational database management system that uses SQL extensibility and standards. | Oracle is an object-relational database management system. It is the first database management developed for grid computing. |
It is developed and implemented in C Language. | It is developed and implemented in C++, C, and assembly language. |
In comparison to Oracle, PostgreSQL is a new database. It was designed by PostgreSQL Global Development Group on 8th July 1996. | In Comparison to PostgreSQL, Oracle is an old database. It was designed by Bob and Larry Ellison. |
PostgreSQL offers good security support but less in comparison to Oracle. | Oracle offers advanced security options. |
PostgreSQL is free to use and open-source. | To use Oracle, you need a license. |
Related article: PostgreSQL vs Oracle |
MongoDB | PostgreSQL |
It is a NoSQL Database. | PostgreSQL is the classic relational database system that endorses all the SQL standards. |
It is developed in C++ programming. | It is developed in C language. |
It is a non-relational database management system. | It is a relational database management system. |
MongoDB is a Document Oriented Database. | PostgreSQL is an Object-Oriented Database |
It is available only in the English Language. | It is available in Multiple Languages. |
The latest version of PostgreSQL is PostgreSQL 16.3, released on 9th May 2024.
The new features of PostgreSQL 16.3 are as follows:
Along with an expert-level knowledge of PostgreSQL, a PostgreSQL Developer also requires a good understanding of Unix scripting, JSON, SQL, and any programming language like Python.
PostgreSQL is a famous database used by different tech giants to store data and maintain back-end applications. These PostgreSQL Interview Questions will evaluate their knowledge and prepare you for job interviews. I hope these questions will help you for your career advancement. If you have any queries, let us know by commenting below.
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Ravindra Savaram is a Technical Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.