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Have you ever wondered what actually happens inside Flutter when you press a button and watch a smooth animation?

Have you ever wondered what actually happens inside Flutter when you press a button and watch a smooth animation?

This article reviews the November 2025 CommitFest.

For the highlights of the previous two CommitFests, check out our last posts: 2025-07, 2025-09.

Planner: eager aggregation
Converting COUNT(1) and COUNT(not_null_col) to COUNT(*)
Parallel TID Range Scan
COPY … TO with partitioned tables
New function error_on_null
Planner support functions for optimizing set-returning functions (SRF)
SQL-standard style functions with temporary objects
BRIN indexes: using the read stream interface for vacuuming
WAIT FOR: waiting for synchronization between replica and primary
Logical replication of sequences
pg_stat_replication_slots: a counter for memory limit exceeds during logical decoding
pg_buffercache: buffer distribution across OS pages
pg_buffercache: marking buffers as dirty
Statistics reset time for individual relations and functions
Monitoring the volume of full page images written to WAL
New parameter log_autoanalyze_min_duration
psql: search path in the prompt
psql: displaying boolean values
pg_rewind: skip copying WAL segments already present on the target server
pgbench: continue running after SQL command errors

Continuing the series of CommitFest 19 reviews, today we're covering the January 2026 CommitFest.

The highlights from previous CommitFests are available here: 2025-07, 2025-09, 2025-11.

Partitioning: merging and splitting partitions
pg_dump[all]/pg_restore: dumping and restoring extended statistics
file_fdw: skipping initial rows
Logical replication: enabling and disabling WAL logical decoding without server restart
Monitoring logical replication slot synchronization delays
pg_available_extensions shows extension installation directories
New function pg_get_multixact_stats: multixact usage statistics
Improvements to vacuum and analyze progress monitoring
Vacuum: memory usage information
vacuumdb --dry-run
jsonb_agg optimization
LISTEN/NOTIFY optimization
ICU: character conversion function optimization
The parameter standard_conforming_strings can no longer be disabled

Today I present results from the first step towards enabling temporary tables in PostgreSQL parallel query execution: benchmarking sequential writes and reads of temp buffers. I added functions to the PostgreSQL system catalog to measure buffer flush operations and ran a set of tests. For the planner, I estimated the cost coefficient of flushing a temporary table buffer page to disk relative to the existing DEFAULT_SEQ_PAGE_COST. I also estimated the cost of a simple scan of temp buffers (a dry-run). Measurements show that sequential writes are about 30% slower than reads. Based on these results, I propose a cost formula. I also ran a limited “dry-run” style estimate and measured write speed when table blocks are distributed across memory pages randomly.

The Art of Comeback of the European Bureaucracy 

On November 26, Members of the European Parliament rejected the Chat Control Act in its current version, i.e, mandatory scanning of the user traffic before it gets encrypted. Lawmakers, however, will hardly give up: requirement for mandatory scanning shall be reconsidered every three years. Xeovo explains what is the story behind this law and why, in reality, there’s little justification for passing it.

In November, 2025 Russia-based web host Media Land was sanctioned by several countries as a bulletproof service — the one hackers relied on to launch DDoS attacks and attack businesses in the United States and in allied countries. “Bulletproof” may refer to a VPN as well, as it usually means abuse resistant and private. Xeovo explains how genuinely reliable anonymous VPNs and hostings differ from bulletproof services — and why the real bulletproof operators are often not those who call themselves that.

There’s a dangerous illusion that “vanilla” open source is a silver bullet for enterprise systems. A real-world stress test of recent years has shown the opposite: when familiar giants like Oracle step aside, plain PostgreSQL often turns into a pumpkin under true enterprise workloads.

Mark Rivkin, Head of technical consulting at Postgres Professional, shares his personal perspective on why teams end up reinventing the wheel — adding millions of lines of code to the core — and why the future belongs to converged database systems.

Disclaimer: this article reflects the author’s independent expert opinion.

In this article, I would like to share my experience participating in the Agentic Legal RAG Challenge 2026 hackathon. Our team is called "Sparks of intelligence".
Original article in Russian: https://habr.com/ru/articles/1014520/