--- title: Postgres MVCC trade-offs dissected, Atlas v1.3 ships... description: Today's standout is a thorough breakdown of PostgreSQL's MVCC design versus undo-log systems like Oracle and InnoDB, covering write amplification, table bloat,... canonical: https://daily.dev/posts/postgres-mvcc-trade-offs-dissected-atlas-v1-3-ships-security-graph-8wpikcxa2 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Postgres MVCC trade-offs dissected, Atlas v1.3 ships security graph | daily.dev og:description: Today's standout is a thorough breakdown of PostgreSQL's MVCC design versus undo-log systems like Oracle and InnoDB, covering write amplification, table bloat,... og:url: https://daily.dev/posts/postgres-mvcc-trade-offs-dissected-atlas-v1-3-ships-security-graph-8wpikcxa2 og:image: https://api.daily.dev/og/posts/8WpIKCxa2.png og:image:alt: Postgres MVCC trade-offs dissected, Atlas v1.3 ships security graph og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Postgres MVCC trade-offs dissected, Atlas v1.3 ships security graph **[Databases Digest](https://daily.dev/sources/databases_digest)** · 4 min read · 0 upvotes · 0 comments ## Summary Today's standout is a thorough breakdown of PostgreSQL's MVCC design versus undo-log systems like Oracle and InnoDB, covering write amplification, table bloat, and what Postgres 19 autovacuum improvements actually change. Atlas v1.3 lands with a security graph that maps database permissions and CVEs with blast-radius tracing, plus lock-safe NOT NULL migrations and 8-10x faster schema tests on PostgreSQL. A RAG postmortem confirms pgvector in an existing Postgres instance is fast enough for most workloads — vector search took under 5ms of a 2.8-second total query time. The Spark alternatives roundup is worth a read if you're still routing Iceberg maintenance or interactive queries through Spark. ## Content **TLDR:** Today's standout is a thorough breakdown of PostgreSQL's MVCC design versus undo-log systems like Oracle and InnoDB, covering write amplification, table bloat, and what Postgres 19 autovacuum improvements actually change. Atlas v1.3 lands with a security graph that maps database permissions and CVEs with blast-radius tracing, plus lock-safe NOT NULL migrations and 8-10x faster schema tests on PostgreSQL. A RAG postmortem confirms pgvector in an existing Postgres instance is fast enough for most workloads — vector search took under 5ms of a 2.8-second total query time. The Spark alternatives roundup is worth a read if you're still routing Iceberg maintenance or interactive queries through Spark. --- ## Postgres MVCC vs undo-log systems: the real trade-offs A deep dive into PostgreSQL's MVCC design covers the four core questions every MVCC implementation must answer and makes the case that undo-log systems (Oracle, MySQL InnoDB) shift costs rather than eliminate them. The charges against Postgres — write amplification, table bloat, long-running transaction issues, 32-bit transaction IDs — are addressed honestly, not dismissed. Also covered: Postgres 19 autovacuum prioritization improvements, the hidden cost of constraints on bulk inserts, and hybrid search patterns combining pgvector with BM25 and reciprocal rank fusion. [Read more](https://daily.dev/posts/5rrouWK54) ## Atlas v1.3: security graph, lock-safe NOT NULL migrations, 8-10x faster schema tests on PostgreSQL Atlas v1.3 ships a security graph that maps the full database attack surface — permissions, misconfigurations, CVEs — with blast-radius tracing. Lock-safe NOT NULL migrations and 8-10x faster schema tests on PostgreSQL are the most operationally relevant additions for teams running frequent schema changes. Atlas Scripts add DataOps-as-code for backfills and GDPR purges with transactional mutations and batched loops. Expanded support lands for Oracle, Snowflake, ClickHouse, MySQL, SQL Server, Azure HorizonDB, and YugabyteDB. [Read more](https://daily.dev/posts/XcV6HiYKZ) ## RAG postmortem: pgvector took 4.9ms of 2,823ms total, dedicated vector DB unnecessary A developer built a RAG system over SEPA payment rulebooks using plain Python and Postgres with pgvector, skipping LangChain and LlamaIndex entirely. Vector search consumed 4.9ms of a 2,823ms total query time — the dedicated vector database case doesn't hold up at this scale. The more useful finding: swapping the LLM is a one-line config change, but changing the embedding model requires re-embedding the entire corpus because dimension constraints mean you can't mix models in the same index. [Read more](https://daily.dev/posts/tFLowBGH8) ## Spark alternatives for the modern lakehouse: nine engines mapped to workloads A practical breakdown of nine Spark alternatives — Flink, Trino, DuckDB, Polars, DataFusion, Ray, dbt/SQLMesh, ClickHouse/StarRocks, and LakeOps — framed around Apache Iceberg as the shared table format. The core argument is that Spark is still the right tool for heavy batch ETL and large-scale distributed shuffles, but using it for Iceberg maintenance, interactive queries, or single-node analytics is expensive and slow. LakeOps is the least-known entry: a Rust/DataFusion-based engine for autonomous Iceberg table maintenance (compaction, orphan cleanup, snapshot expiration). [Read more](https://daily.dev/posts/EO0OaQ4kc) --- ## Also notable - **Oracle query optimization: cost dropped from 11,711 to 7,465, but 6M-row scan remains:** Rewriting a TO_CHAR-wrapped column filter to bare date comparisons with TRUNC and adding a covering index on the orders table cut Oracle query cost from 11,711 to 7,465 — but the order_items full table scan (cost 6,493, 6M rows) is unfixable without either a five-column covering index or partitioning via denormalization. [Read more](https://daily.dev/posts/8p7j9jU7y) - **Database metastability: two independent controllers can create a positive feedback loop under overload:** A paper from ICCCN'26 shows that two independently sensible ticket-based concurrency controllers — one per queue — can reward churn over real progress under overload, inflating tickets and crowding the CPU; the fix is freezing the long queue's tickets at a static value and using a single controller with an ungameable signal. [Read more](https://daily.dev/posts/hVjD1hRfq) - **Syncular: offline-first SQL sync with SQLite client, Postgres/D1 server backends, TypeScript and Rust cores:** Syncular is an open-source offline-first sync library where clients hold a real local SQLite database, writes flow through an optimistic outbox, and a single ordered commit log on the server is the source of truth — supporting Postgres, SQLite, and Cloudflare D1 as server backends with per-column E2EE and Yjs CRDT merging. [Read more](https://daily.dev/posts/tz99jaUTz) ## Similar posts on daily.dev - [PostgreSQL's MVCC is bad. So is everyone else's.](https://daily.dev/posts/postgresql-s-mvcc-is-bad-so-is-everyone-else-s--0puk6jb2f) · Planet PostgreSQL · 13 upvotes · 0 comments - [Database Transactions — PlanetScale](https://daily.dev/posts/database-transactions-planetscale-ubjf1ictb) · Hacker News · 1 upvotes · 0 comments --- Tags: [#backend](https://daily.dev/tags/backend), [#postgresql](https://daily.dev/tags/postgresql), [#pgvector](https://daily.dev/tags/pgvector) [View this post on daily.dev](https://daily.dev/posts/postgres-mvcc-trade-offs-dissected-atlas-v1-3-ships-security-graph-8wpikcxa2) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/postgres-mvcc-trade-offs-dissected-atlas-v1-3-ships-security-graph-8wpikcxa2","headline":"Postgres MVCC trade-offs dissected, Atlas v1.3 ships security graph","text":"Today's standout is a thorough breakdown of PostgreSQL's MVCC design versus undo-log systems like Oracle and InnoDB, covering write amplification, table bloat, and what Postgres 19 autovacuum improvements actually change. 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