PostgreSQL: Why it is used for and how it works?

The ORDBMS mainly helps both relational and non-relational querying. It follows SQL programming standards and includes enhancements to effectively handle complex queries and large database applications.

Why use PostgreSQL?

If you check, it is an ACID compliant, which confirms consistent transaction processing. Following these rules is important. This ensures that all transactions can be accessed smoothly.
It also helps to keep the database intact. This is important even if the system crashes.

Open source relational database and cost-effective
One of the essential reasons for PostgreSQL’s familiarity is that it is free and open Source, and the usage is free. At the same time, you will feel that the solution you get will be cost-effective for different sizes for all types of businesses.
Many developers help improve open-source software, keeping it current with new technology.

Advanced-Data Types

PostgreSQL supports various advanced data types involving XML, and JSON, allowing the efficient handling of structured and semi-structured data. Also, this makes it better for applications demanding the storage and manipulation of respective data structures.

Strong Support for Standards

It mainly follows SQL standards, confirming compatibility with SQL-based tools and systems. This compatibility makes it easier for developers to transition to PostgreSQL from other database systems and integrate it with various software applications.

Extensibility
The extensibility allows users to define their functions, operators, and data types. This flexibility makes it appropriate for various applications and complex data warehousing solutions.  Also, users can extend capabilities by including custom functions.

Complete Community and Documentation Support
It claims complete documentation and a vast, active community that delivers support through mailing lists, forums, and other channels. For information, this vast support network helps users troubleshoot problems and stay informed about the latest developments and top practices.

Robust Scalability and Performance
For information, it is designed to handle high concurrency workloads and massive datasets capably. It also supports various performance optimization techniques, like partitioning, query optimization and indexing.
Also, PostgreSQL’s capability to scale horizontally and vertically makes it appropriate for applications that demand high scalability and performance.

How does PostgreSQL work?
If you want to understand how it works, it is crucial to delve into its key components and architecture. The architecture of PostgreSQL offers different processes and components to handle together and process data proficiently.

PostgreSQL Architecture

It is essential to know that PostgreSQL follows a client-server architecture, where the server handles the database and processes requests from the client. The architecture is primarily divided into the following components.

Postmaster: Postmaster is the primary process in PostgreSQL and manages and initialises processes. At the same time, it also handles client connections, confirms smoother operations, and begins the required backend processes.
Shared Memory: It is the vital component, which stores data that requires access by multiple processes. Also, it includes different caches and buffers, such as lock tables, write-ahead logs and shared buffer cache.

Background Processes: PostgreSQL employs various background processes when performing different tasks, such as managing auto vacuum, handling vacuuming and managing WAL. Also, you should know that some of the critical background processes contain:

Checkpointer: Confirms that the data files are coordinated with the WAL records.

Background Writer: Writes dirty buffers to disk to maintain buffer cache efficiency.

WAL Writer: Confirms that WAL records are mainly effectively written to the disk.

Autovacuum Daemon: Reclaiming storage by removing outdated data automatically.

Data Storage

PostgreSQL mainly stores data in tables, which are organized into schemas and can utilize stored procedures for additional functionality. For information, each table comprises rows and columns, each representing a record and the column representing a field.

At the same time, you need to know that PostgreSQL utilizes a combination of stack storage and indexing to handle data competently.

Heap Storage: If you check, heap storage is the primary storage method, storing data in unordered blocks. It is essential to know that each table has a heap file, and each row in the table is stored in a separate block within the heap file.

Indexing: PostgreSQL supports different indexing methods. It is essential to know that indexes improve query performance by letting the database locate particular rows rapidly. It will update indexes as data is updated, inserted or deleted, confirming that they stay efficient.

Query Processing
Query processing includes execution, optimization, planning and parsing. The process can be handled in the below stages:

Parsing: PostgreSQL transforms the SQL query into an abstract syntax tree during the parsing stage. For information, the parser checks the query regarding syntax errors and verifies that the referenced columns and tables exist.

Planning: When it is in the planning stage, it generates a query plan, a sequence of steps needed to implement the query. If you check with the planner, it mainly considers different factors, such as the data distribution, join conditions and availability of indexes, to define the effectual execution plan.

Optimization: The optimizer improves the query plan by considering alternative execution strategies and choosing the one with the least estimated rate. It utilizes a cost-based optimization approach, considering factors like memory usage, CPU and I/O.

Execution: When it comes to the execution stage, it follows the query plan to repossess the data requested. The executor processes the steps in the plan, accessing data from indexes and tables as required and returning the outcome to the client.

Concurrency and Transactions Control
PostgreSQL supports transactions, which are orders of SQL statements that are implemented as a single unit. Transactions mainly ensure data integrity by delivering durability, isolation, consistency, and atomicity. It uses a locking mechanism and multiversion concurrency control to handle concurrent transactions.

MVCC:
MVCC mainly allows PostgreSQL to offer concurrent access to the database without demanding wide locking. Each transaction operates on a database snapshot, ensuring a consistent view of the data is essential. For your information, changes made by one transaction become visible to other transactions once those changes are committed.

Locking:
PostgreSQL utilizes different types of locks, such as advisory, table, and row-level locks, to handle concurrent access to data. The lock manager confirms that transactions obtain the required locks before preventing conflicts, ensuring data consistency and accessing data.

Backup and Recovery
PostgreSQL offers recovery mechanisms and strong backups to ensure data availability and protection. Let’s have a look at the essential features contain:

Point-in-Time Recovery:
PITR allows users to reinstate the database to a particular point using the right combination of WAL archives and base backups. This feature is crucial when recovering from data corruption or accidental data loss.

Logical Replication:
Logical replication lets users replicate data at the logical level, enabling selective replication of postgresql databases and tables. This essential feature is highly used for data distribution, analytics and data warehousing across different locations.

Physical Replication:
Physical replication includes copying the complete database cluster, including WAL records and data files. This method offers high redundancy and availability by maintaining a standby server that will take over if any primary server failure occurs.