Postgres^®: The world's most-loved database

EDB contributed periodic checkpoints during WAL recovery—the technical foundation for a database that could survive a crash and come back intact. The principle: no data left behind.

The year Apple introduced the iPhone, permanently raising the bar on what performance at scale meant. EDB contributed Heap Only Tuples, reducing table bloat on high-write workloads. Busy systems stayed fast.

pg_get_keywords gave management tools version agility—the ability to understand keywords across different Postgres versions without hard-coding them. A small feature. A large operational improvement for anyone managing multiple environments.

Hot standby arrived: fundamental support for read-only queries and crash recovery. Combined with in-place version upgrades, downtime during major version transitions dropped by orders of magnitude.

Linear read scalability to 64 cores brought Postgres fully into the modern hardware era. Synchronous replication laid the foundation for high availability with zero data loss.

Index-only scans made query execution more efficient. MySQL Foreign Data Wrappers opened a practical migration path for organizations ready to move.

Materialized views arrived—database views stored as tables, accelerating access to frequently queried data. The first serious signal that Postgres could compete on analytics.

Concurrently updatable materialized views, pg_prewarm, and ALTER SYSTEM deepened both analytical capability and operational control. MongoDB and Hadoop foreign data wrappers extended Postgres's reach into heterogeneous data environments.

The year OpenAI was founded—the same year EDB contributed the parallelism infrastructure that would eventually serve the AI workloads no one had yet built. Sorting, in-memory hash, and concurrency locking improvements made standard operations measurably faster.

Parallel Query made large dataset operations faster by distributing query execution across CPU cores. Synchronous replication enhancements laid the groundwork for five-9s availability.

Logical replication, parallel query improvements, durable hash indexes, and postgres_fdw pushdown of joins and aggregates. Postgres became a serious distributed data platform.

The year GDPR took effect, codifying the principle that organizations must control their own data. Postgres responded with JIT compilation for improved query performance, and EDB contributed runtime partition pruning, stored procedures, and deeper parallelism — the infrastructure for production-grade, compliance-capable deployments.

Pluggable table storage capability arrived, providing genuine flexibility in how data is stored and retrieved. The engine became more modular, and more adaptable.

As organizations worldwide shifted to distributed operations, Postgres focused on what distributed systems demand: pg_verifybackup for auditable backup integrity, logical replication improvements for larger workloads, and incremental sorting for efficient large-dataset queries.

Server Name Indication in SSL connections, SCRAM-SHA-256 as the default authentication, and distinguished name matching for client certificate authentication. Security hardening at the protocol level.

MERGE support removed a major obstacle for teams migrating from legacy databases. Column and row filtering for selective replication gave organizations finer-grained control over what data moves where.

The year India surpassed China as the world's most populous country—a reminder that data infrastructure now operates at a scale that was unimaginable when Postgres was born. Non-superuser subscription management and safer role creation made Postgres a serious DBaaS platform, ready for the operational complexity of global deployments.