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logical replication

The database storage problem is solved. Here’s what comes next.
Tech Optimizer
June 25, 2026

The database storage problem is solved. Here’s what comes next.

Postgres has been a reliable transactional database for three decades, used for managing customer records and financial transactions. Innovations in the Postgres ecosystem are now focused on minimizing data movement rather than just data storage. The challenge of interoperability is becoming crucial, as organizations seek to share operational data seamlessly across various systems without creating additional copies or pipelines. Many organizations are spending as much effort on data movement as on data storage. Postgres is increasingly viewed as the authoritative system for critical information, and its role is evolving to facilitate better interaction with operational data. Technologies like logical replication and change data capture are enhancing Postgres's integration within data ecosystems. The rise of AI has highlighted the need for real-time access to operational data and has prompted organizations to reconsider the necessity of maintaining multiple copies of the same data. The database industry is shifting focus from optimizing storage to enabling effortless data sharing across systems. Postgres continues to adapt to new workloads and architectural patterns, maintaining its reputation as a stable foundation for operational data while expanding its capabilities through innovative extensions.
Millisecond Latency at Scale: Why Our ML Feature Store Runs on Snowflake Postgres
Tech Optimizer
June 23, 2026

Millisecond Latency at Scale: Why Our ML Feature Store Runs on Snowflake Postgres

Organizations are consolidating their fragmented database environments with Snowflake Postgres, phasing out outdated systems and simplifying multivendor setups without extensive code rewrites. Ericsson migrated four legacy databases to Snowflake Postgres, achieving a 99% reduction in data processing time. SimCorp's transition to Snowflake Postgres resulted in a tenfold increase in disk operation speeds. Sigma Computing provides real-time analytics using Snowflake Postgres, eliminating the need for external systems. BlueCloud supports low-latency transactional workloads and analytics on a single platform. Superblocks enables developers to create full-stack applications using Snowflake CoCo, leveraging SQL tools against live data. Snowflake Postgres is approximately four times faster than Databricks Lakebase and has a 99.95% published uptime SLA. It operates on Postgres 18 and accommodates up to 64 TB of storage, surpassing Lakebase's 16 TB limit. Snowflake Postgres simplifies management with in-place major version upgrades and supports standard logical replication, enhancing flexibility for data movement and integration.
PostgreSQL 18 on Amazon Aurora and Amazon RDS: Security, monitoring, and developer enhancements
Tech Optimizer
June 20, 2026

PostgreSQL 18 on Amazon Aurora and Amazon RDS: Security, monitoring, and developer enhancements

PostgreSQL version 18 has deprecated MD5 password authentication in favor of SCRAM-SHA-256, with a new parameter, md5_password_warnings, enabled by default to log deprecation warnings. It has enhanced monitoring capabilities by adding columns to pg_stat_database and pg_stat_statements to track parallel worker activity, with the default max_parallel_workers_per_gather set to 0 in Aurora PostgreSQL. The pg_stat_subscription_stats view now includes new columns for tracking conflict types in logical replication. Optimizer statistics are automatically transferred during upgrades, while uuidv7() generates timestamp-ordered UUIDs. The default streaming option for CREATE SUBSCRIPTION has changed to parallel, and the idle_replication_slot_timeout parameter automatically invalidates inactive replication slots. Enhancements to the COPY command include REJECT_LIMIT for error tolerance and a silent LOG_VERBOSITY level. OLD and NEW aliases have been introduced in RETURNING clauses for various DML commands.
PostgreSQL 18 on Amazon Aurora and Amazon RDS: Performance enhancements
Tech Optimizer
June 20, 2026

PostgreSQL 18 on Amazon Aurora and Amazon RDS: Performance enhancements

PostgreSQL 18 addresses common performance challenges for users, including managing query performance across composite indexes, diagnosing memory spills in materialized Common Table Expressions (CTEs), and upgrading major versions without plan regressions. Key enhancements include skip scan optimization for multicolumn indexes, improved EXPLAIN functionality, and optimizer statistics that persist through major version upgrades. Skip scan optimization allows PostgreSQL to efficiently utilize multicolumn B-tree indexes even when leading columns are not specified in the WHERE clause, significantly improving query performance. The EXPLAIN command has been enhanced to include buffer statistics by default, providing deeper insights into query execution and resource usage. PostgreSQL 18 also introduces visibility into the storage of materialized nodes in query plans, indicating whether intermediate results were stored in memory or spilled to disk. A new metric, Index Searches, has been added to EXPLAIN ANALYZE output, indicating how many times the database traversed the index tree during query execution. Additionally, Self-Join Elimination (SJE) automatically detects and removes unnecessary inner joins of a table to itself, optimizing query performance. The autovacuum mechanism has been improved with the introduction of autovacuum_vacuum_max_threshold, which caps the number of dead tuples that can accumulate before autovacuum triggers a VACUUM, addressing issues with large tables. The vacuum_truncate parameter provides a server-wide control point to disable VACUUM’s file truncation behavior, reducing locking issues on busy systems. PostgreSQL 18 also separates the allocation of autovacuum worker slots from their usage, allowing for dynamic adjustments to autovacuum_max_workers without requiring a server restart. Finally, new columns in pg_stat_all_tables track cumulative time spent on maintenance operations, providing better insights into maintenance overhead for each table.
Looking Ahead to Postgres 19
Tech Optimizer
June 19, 2026

Looking Ahead to Postgres 19

Postgres has introduced new functionalities, including UPDATE and DELETE FOR PORTION OF, enhancing temporal use cases. The expansion of RANDOM() temporal functions is attributed to Paul Ramsey and Greg Sabino Mullane. Version 19 includes performance improvements in the planner and executor components, with contributions from Tom Lane. Key enhancements include refinements in anti-joins and semi-joins, constant folding optimizations, incremental sorting with append paths, enhanced aggregate processing prior to joins, improved join selectivity computation, and more comprehensive function statistics. These changes allow Postgres to better understand query structures, reducing unnecessary processing. The visibility of memoization in EXPLAIN has improved, sort performance has benefited from radix sort, and foreign key constraint checks have become faster. The COPY FROM command can now utilize SIMD instructions. Postgres 19 offers a range of improvements for application developers, operators, performance enthusiasts, and those building on Postgres, including enhanced graph queries, refined SQL syntax, improved window functions, better upsert behavior, REPACK CONCURRENTLY, advancements in autovacuum, improved monitoring capabilities, and new hooks. The release is still in beta, providing an opportunity for testing applications, migration, extensions, execution plans, and maintenance workflows.
PostgreSQL Flaws Expose Databases to Remote Code Execution and SQL Injection
Tech Optimizer
May 21, 2026

PostgreSQL Flaws Expose Databases to Remote Code Execution and SQL Injection

PostgreSQL has released versions 18.4, 17.10, 16.14, 15.18, and 14.23 to address 11 security vulnerabilities and over 60 bugs. The vulnerabilities affect PostgreSQL versions 14 through 18 and include issues such as remote code execution, SQL injection, and denial-of-service risks. Specific vulnerabilities include: - CVE-2026-6472: Missing authorization in CREATE TYPE allows query hijacking. - CVE-2026-6473: Integer wraparound leads to out-of-bounds writes and server crashes. - CVE-2026-6474: Format string issue leaks server memory. - CVE-2026-6475: Symlink attack allows overwriting arbitrary files. - CVE-2026-6476: SQL injection allows execution of arbitrary SQL as superuser. - CVE-2026-6477: Memory buffer overwrite via libpq lo_* functions. - CVE-2026-6478: Timing attack exposes MD5-hashed passwords. - CVE-2026-6479: SSL/GSS recursion flaw allows denial-of-service. - CVE-2026-6575: Buffer over-read leaks memory data (PostgreSQL 18 only). - CVE-2026-6637: Refint module enables stack overflow and SQL injection, leading to possible RCE. - CVE-2026-6638: SQL injection in REFRESH PUBLICATION via table names. Organizations are advised to upgrade to the latest versions, avoid MD5 password authentication, restrict privileges, audit extensions, and monitor for abnormal activity. PostgreSQL 14 will reach its end-of-life on November 12, 2026.
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