---
title: "Postgres"
description: "308 posts about Postgres, summarised, each linking to the original."
---

# Postgres
> 308 posts about Postgres, summarised, each linking to the original.

## Articles

### [From monolith to Lakebase to LTAP: rethinking the database from storage up](https://yomu.fyi/post/from-monolith-to-lakebase-to-ltap-rethinking-the-database-from-storage.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Reynold Xin
- Published: Jun 30, 2026
- Type: Explainer

The post examines why monolithic OLTP databases become fragile and difficult to scale when compute, the write-ahead log (WAL), and data files share one machine. Using Postgres as its primary example, it contrasts local WAL durability and physical cloning with Lakebase, whose stateless Postgres compute externalizes those components into SafeKeeper and PageServer services. SafeKeeper replicates log records across a quorum through Paxos-based network replication, while PageServer applies the WAL and materializes data in cloud object storage. The resulting separation is presented as a way to improve durability, independently scale reads and writes, isolate workloads, and support high availability and branching without physical database clones. LTAP extends the design by making transactional tables directly queryable for analytics from a single governed copy, avoiding CDC or mirroring and allowing transactional and analytical engines to scale independently.


### [ClickHouse is now a native connection in Notion Custom Agents](https://yomu.fyi/post/clickhouse-is-now-a-native-connection-in-notion-custom-agents.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 25, 2026
- Type: Announcement

ClickHouse is now a native, preconfigured connection in Notion Custom Agents, allowing agents to access ClickHouse Cloud data without leaving Notion. After an OAuth connection, agents can explore schemas, translate plain-language questions into ClickHouse SQL, run read-only queries, and return results in the workspace. The connection exposes 14 read-only tools covering databases and tables, SELECT queries against ClickHouse and Managed Postgres, and organization, service, ClickPipes, backup, and cost information; users can set each tool to run automatically or require approval. Custom Agents can run on a schedule, including a daily observability report that queries error rates, p99 latency, and request volume from a Managed ClickStack service. The connector is in beta and requires a ClickHouse Cloud service with Remote MCP enabled plus a Notion Business or Enterprise workspace.


### [Why we rewrote WAL-G for Postgres backups in Rust: Meet WAL-RUS](https://yomu.fyi/post/why-we-rewrote-wal-g-for-postgres-backups-in-rust-meet-wal-rus.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 25, 2026
- Type: Problem & solution

ClickHouse Cloud built WAL-RUS, an open-source Rust implementation of PostgreSQL backup and WAL archival tooling, after encountering difficulty predicting WAL-G’s memory usage in resource-constrained environments. The project preserves WAL-G’s core functionality and compatibility while using bounded worker pools, controlled concurrency, persistent object-storage connections, and a streaming pipeline that limits buffering and data copies. It uses the same WALG\_ configuration variables, and WAL-G and WAL-RUS can read each other’s archives. In a sustained WAL-heavy benchmark with four archival workers, WAL-RUS stayed below 1 GB of peak virtual memory versus nearly 2.8 GB for WAL-G, while both maintained minimal backlog and comparable CPU usage. The authors plan to make WAL-RUS the default backup and archival mechanism for ClickHouse Cloud’s managed Postgres offering and are working to upstream its Postgres 17 wal summaries support to WAL-G.


### [How Vibe.co handles billions of ad impressions with ClickHouse Cloud](https://yomu.fyi/post/how-vibe-co-handles-billions-of-ad-impressions-with-clickhouse-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 25, 2026
- Type: Problem & solution

Vibe.co, recently acquired by Walmart, uses ClickHouse Cloud to provide real-time campaign reporting for thousands of Connected TV advertisers across billions of ad impressions. It migrated from Postgres after aggregation-heavy OLAP queries made its pre-aggregation layer a bottleneck, limiting interactive slicing and requiring new jobs for reporting use cases. The team evaluated self-hosted ClickHouse, another managed option, and ClickHouse Cloud, choosing the latter for operational simplicity, support from ClickHouse engineers, and separation of storage and compute with more predictable costs. Vibe uses refreshable materialized views for hot/cold tiering, keeping the last 30 days in a hot table; stored data grew from about 100 GB to over 2 TB without rearchitecting, while more than 90% of client campaign reports respond in under 100ms.


### [What To Look For in a Serverless Database for AI Applications](https://yomu.fyi/post/what-to-look-for-in-a-serverless-database-for-ai-applications.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Jun 25, 2026
- Type: Explainer

Serverless databases are presented as a baseline for AI applications whose traffic can be volatile, idle for long periods, or spike when agents fan out queries. The guide distinguishes managed serverless systems from autoscaling products by focusing on architectural separation of compute and storage, true scale-to-zero, cold-start behavior, connection handling, pricing, performance, portability, governance, and AI capabilities such as vector search. It recommends evaluating both low- and high-utilization costs, published warm-up times, tail latency (p95/p99), and built-in pooling or HTTP/Data APIs for high-concurrency agents and serverless functions. The text positions Lakebase as an example that combines serverless Postgres, shared lakehouse storage, and Unity Catalog governance, and cites reported cost and management reductions from a 2025 study while noting that provisioned deployments may suit continuously high-throughput workloads.


### [What Is Serverless PostgreSQL?](https://yomu.fyi/post/what-is-serverless-postgresql.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Jun 25, 2026
- Type: Explainer

Serverless PostgreSQL is presented as a fully managed cloud database model that decouples compute and storage, allowing each to scale independently with demand. Traditional deployments require teams to size infrastructure, manually manage scaling, and absorb costs from idle capacity. In serverless systems, the provider provisions compute on demand, can suspend it when idle, and bills according to active usage; scale-to-zero may introduce cold-start latency. The architecture can also support database branching through copy-on-write, creating isolated environments without duplicating data. The article distinguishes this model from lakebase architecture, which combines transactional and analytical workloads on a shared foundation using decoupled compute, durable object storage, log-based storage systems, and orchestration.


### [Databricks positioned highest in execution and furthest in vision for the second consecutive year in Gartner Magic Quadrant](https://yomu.fyi/post/databricks-positioned-highest-in-execution-and-furthest-in-vision-for.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Craig Wiley, Kasey Uhlenhuth, Kayli Berlin, Cynthya Peranandam
- Published: Jun 24, 2026
- Type: Announcement

Databricks says Gartner positioned it highest for execution and furthest for vision in the Magic Quadrant for the second consecutive year. The post connects this recognition to a category reclassified from “Data Science and Machine Learning” to “AI Platforms for Data Science and Machine Learning,” and argues that agentic applications require enterprise data, governance, observability, and business context. Databricks presents a unified approach combining the lakehouse, Lakebase, Agent Bricks, Unity Catalog, and Unity AI Gateway to build, monitor, and govern agents, models, data, apps, and tools. Reported examples include YipitData’s 20x increase in company coverage with 92–95% tagging accuracy, Block’s unified AI and data estate, and Novo Nordisk’s attribution of more than $157 million in net new value to governed clinical-trial optimization.


### [What's New in pg\_clickhouse v0.3.2: Postgres 19, TLS, Regex, and Memory](https://yomu.fyi/post/what-s-new-in-pg-clickhouse-v0-3-2-postgres-19-tls-regex-and-memory.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 23, 2026
- Type: Announcement

pg\_clickhouse v0.3.2 updates the Postgres interface for querying ClickHouse, with changes centered on PostgreSQL 19 Beta1 support, TLS configuration, regular-expression pushdown, and memory consumption. The release adds CREATE SERVER options for forcing TLS or plaintext, selecting a minimum TLS version, and enabling ClickHouse native-protocol compression. Revised pushdown logic maps Postgres regular-expression flags to ClickHouse behavior, while regexp\_match() can now be pushed down when its pattern has no capturing groups. Two memory issues were fixed: one involving unbuffered HTTP-driver queries and another involving repeated foreign scans such as parameterized inner scans in nested-loop joins. The minor update requires no reload, restart, or ALTER EXTENSION UPDATE, and also fixes empty-array ANY() errors on ClickHouse versions before 25.


### [What's new in Postgres Managed by ClickHouse: RBAC, Terraform, ClickPipes, extensions, and more](https://yomu.fyi/post/what-s-new-in-postgres-managed-by-clickhouse-rbac-terraform-clickpipes.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 18, 2026
- Type: Announcement

Postgres managed by ClickHouse, which entered public beta in May, received a broad update covering console operations, per-service RBAC, Terraform, Stripe provisioning, ClickPipes migrations, billing, capacity reservations, and extensions. The redesigned console adds service health, resource, and query views, while RBAC provides View and Manage roles across the console and public REST API; the alpha Terraform provider covers lifecycle operations including resizing, HA, replicas, restore, and password rotation. Postgres-to-Postgres ClickPipes now automate schema migration, usage is integrated into ClickHouse Cloud’s metering and billing, and AWS capacity reservations are allocated dynamically across availability zones. Underneath, pg\_clickhouse and pg\_stat\_ch moved to the header-only clickhouse-c library, removing a C++ exception conflict, using Postgres memory contexts, and reducing the x86-64 Linux extension binary from 4.9 MB to 1.4 MB; the update shipped less than a month after beta, with Terraform and extensions still evolving.


### [The open ecosystem around ClickHouse](https://yomu.fyi/post/the-open-ecosystem-around-clickhouse.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 17, 2026
- Type: Explainer

ClickHouse’s open ecosystem spans clients, dashboards, ingestion pipelines, projects built on its engine, and agents that query it, with 2,600+ contributors, 240,000+ commits, and hundreds of millions of downloads cited. It describes open standards including OpenTelemetry for observability, Model Context Protocol (MCP) for AI tooling, and Iceberg and Delta Lake for lakehouse data, plus Iceberg REST catalogs, Apache Polaris, and Unity Catalog. The surrounding stack includes ClickStack, chDB, Langfuse, LibreChat, official language clients, a Kubernetes operator, Postgres bridges such as PeerDB and pg\_clickhouse, and integrations with Airflow, dbt, Grafana, Fivetran, and Sigma. Specific updates include full Iceberg v2 support, Iceberg writes in 25.8, Paimon in 25.10, chDB v4’s DataStore API, and a Python client v1.0 with native async and 4x faster cold starts. The post frames this openness as supporting flexible tooling and community-led growth, reporting more than 200 integrations while noting that the ecosystem’s next direction remains unknown.


### [What’s coming next to Free Edition](https://yomu.fyi/post/what-s-coming-next-to-free-edition.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Will Valori, Trang Le
- Published: Jun 17, 2026
- Type: Announcement

Databricks is expanding Free Edition, launched twelve months ago to help people learn modern data and AI, after providing more than $10M in credits to over 500,000 learners. The five additions are Genie Code, serverless GPUs subject to availability, Lakebase, Agent Bricks, and Lakeflow Designer. Genie Code can generate, run, interpret, and refine code autonomously for tasks such as dataset analysis, pipeline cleaning, and visualization, while GPUs support deep-learning workloads including training, fine-tuning, inference, and large-dataset processing. Lakebase adds a fully managed Postgres-compatible database for data apps and AI agents; Agent Bricks supplies composable tools, memory, orchestration, and evaluation; and Lakeflow Designer enables visual pipeline construction. Together, these additions are presented as a complete free toolkit covering data engineering, analytics, machine learning, app development, and AI agents, allowing users to build end-to-end data and AI projects in Free Edition.


### [92x faster queries: How Open Electricity uses ClickHouse to track Australia’s energy transition in real time](https://yomu.fyi/post/92x-faster-queries-how-open-electricity-uses-clickhouse-to-track-austr.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 17, 2026
- Type: Problem & solution

Open Electricity uses ClickHouse to serve live Australian energy data through a public platform and API spanning roughly one billion records. Migrating from Postgres and TimescaleDB addressed queries that could take more than five minutes, reducing a benchmark to just over three seconds and to 60 milliseconds with a materialized view. The new setup keeps heavy relational workloads in Postgres while ClickHouse handles analytics, using ReplacingMergeTree base tables and more than 20 materialized views for different aggregation patterns. It also uses substantially less hardware than the previous configuration: four cores, four GB RAM, and 200 GB disk versus 16 cores, 32 GB RAM, and 1.6 TB, while serving data added daily and API users.


### [Announcing Lakebase Search: agent-native retrieval built into Lakebase Postgres](https://yomu.fyi/post/announcing-lakebase-search-agent-native-retrieval-built-into-lakebase.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Pranav Aurora, Zhou Sun, Jinjing Zhou
- Published: Jun 16, 2026
- Type: Announcement

Lakebase Search is a beta offering on AWS and Azure that adds hybrid vector and full-text retrieval to Lakebase Postgres. It uses the lakebase\_vector and lakebase\_text extensions to keep retrieval, memory, operational data, and hybrid search in one backend. lakebase\_vector retains pgvector types and operators, applies RaBitQ clustering and compression for 32x smaller indexes, and targets more than 1B vectors, while lakebase\_text replaces GIN with object-storage-optimized BM25 ranking. A tiered cache keeps hot data on NVMe and places colder data in object storage; the source reports lower memory needs, faster index builds, and cold-cache startup than standard pgvector HNSW in its LAION-100M benchmark. The extensions also combine vector similarity and keyword relevance with reciprocal rank fusion in a single SQL query, enabling joins and tenant filtering alongside transactional workflows.


### [Unifying Data and Governance in the Agentic Era: What’s New with Azure Databricks](https://yomu.fyi/post/unifying-data-and-governance-in-the-agentic-era-what-s-new-with-azure.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Isaac Gritz, Toussaint Webb, Ben Tripp, Kiriana Stukas
- Published: Jun 16, 2026
- Type: Announcement

At Data + AI Summit 2026, Azure Databricks announced capabilities aimed at moving enterprises from experimental AI pilots to production-grade automated workflows by unifying data, productivity tools, marketing, and governance on Azure. Its Agentic Data foundation introduces LTAP, combining analytical data, streaming pipelines, and live application transactions in one lakehouse storage copy; Lakebase adds a managed serverless Postgres engine with copy-on-write branching, while Lakehouse//RT targets millisecond responses for high-concurrency workloads. Genie integrations for Microsoft Teams, M365 Copilot, Excel, and SharePoint bring governed lakehouse intelligence and ingestion into daily work, alongside tools for agents, applications, pipelines, and autonomous operations. CustomerLake adds Profile Agents and Campaign Agents for customer profiles and personalization, while Genie Ontology and Unity AI Gateway provide semantic context, rate limits, content filtering, and spend controls.


### [What a difference 10 years of open source makes](https://yomu.fyi/post/what-a-difference-10-years-of-open-source-makes.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 16, 2026
- Type: Explainer

ClickHouse marks ten years since becoming open source under the Apache 2.0 license, crediting more than 2,600 contributors and a decade of monthly releases for its growth into one of the world’s most widely deployed analytical databases. Recent engineering work spans joins, updates and deletes, JSON, full-text search, vector search, query acceleration, integrations, and developer tooling. Join-focused changes made the TPC-H SF100 workload 26× faster between versions 22.4 and 26.4, while statistics-based reordering reduced one six-table query from 3,903.7 seconds to 2.7 seconds. The project also publishes open benchmarks, including ClickBench, JSONBench, CostBench, and PostgresBench, with scripts, configurations, data, and results intended for independent validation. Its next phase continues to emphasize community contributions and broader ways to use ClickHouse.


### [Ten years of ClickHouse in open source](https://yomu.fyi/post/ten-years-of-clickhouse-in-open-source.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 15, 2026
- Type: Explainer

ClickHouse’s tenth-anniversary history describes its path from an internal web-analytics experiment to an open-source analytical database with more than 2,000 contributors. The original problem was processing rapidly growing, real-time logs while answering flexible reports quickly; tested MySQL extensions and standalone analytical databases did not meet the stated scale of 100 billion records per day and 500 columns. The project built column-oriented storage, lightweight compression, custom aggregation structures, background merges, and query support for grouping, aggregation, filtering, and sorting. Released publicly on June 15, 2016, ClickHouse is presented as a level-three open-source project with public contribution guidelines, code review, testing, CI, documentation, and a roadmap, while contributors receive credit even when implementations are substantially rewritten.


### [Better, faster, less wrong: Enhancing issue grouping](https://yomu.fyi/post/better-faster-less-wrong-enhancing-issue-grouping.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Kush Dubey, Yuval Mandelboum
- Published: Jun 12, 2026
- Type: Problem & solution

Sentry upgraded its AI-driven issue grouping system to better prevent duplicate issues without merging distinct application errors. The team trained lightonai/modernbert-embed-large using Matryoshka Representation Learning on hundreds of thousands of stacktrace pairs labeled by Claude Sonnet 4.5. To optimize the high-throughput ingestion pipeline, embeddings were truncated from 768 to 64 dimensions, combined with bfloat16 precision, PyTorch SDPA, and CUDA graph compilation. A phased live rollout used threshold-gated index backfilling and automatic fallback to prevent issue spikes during migration. In production, the v2 model cuts the overgrouping rate from 8% to 4%, increases prevented duplicate issues to 70%, and delivers 6x faster inference.


### [Introducing Postgres to Postgres ClickPipes in ClickHouse Cloud](https://yomu.fyi/post/introducing-postgres-to-postgres-clickpipes-in-clickhouse-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 11, 2026
- Type: Announcement

Postgres-to-Postgres migrations between providers can require manual schema handling, data movement, CDC, and cutover coordination, with risks around database objects and long-running loads. Postgres to Postgres ClickPipes, now in public beta, provides a fully managed migration service in ClickHouse Cloud designed to reduce operational overhead and support minimal downtime. It automates schema dump and restore, including secure connections, role conflicts, version differences, transactional application, retries, and UI or notification-based error reporting, while PeerDB supplies parallel initial loads and CDC capabilities. Independent pull and push processes use retries and alerting for transient errors, and the roadmap includes features to assist with cutover into Postgres by ClickHouse.


### [Agents can now provision ClickHouse and Postgres on ClickHouse Cloud](https://yomu.fyi/post/agents-can-now-provision-clickhouse-and-postgres-on-clickhouse-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 10, 2026
- Type: Announcement

ClickHouse Cloud is now available through Stripe Projects, a Stripe CLI workflow that lets developers and AI agents provision real infrastructure from the command line. Running stripe projects init my-app and adding a service provisions ClickHouse or managed Postgres, returns working credentials to the environment through .env, and hands control to clickhousectl; clickhousectl greater than v0.3.0 is required. The integration supports ClickHouse for real-time analytics and managed Postgres, identified as a public beta, for transactional workloads; both services use the same CLI workflow, land in the same account, and share credentials, while Postgres uses local NVMe storage and is described as offering microsecond latency and up to 10x faster performance on I/O-heavy workloads. The feature is in developer preview, and agents can continue through clickhousectl for data ingestion with ClickPipes and service queries without manual credential handling or context switching.


### [What's new in clickhousectl v0.3.0](https://yomu.fyi/post/what-s-new-in-clickhousectl-v0-3-0.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 9, 2026
- Type: Announcement

clickhousectl v0.3.0 adds improvements aimed at agentic workflows, additional installation methods, OAuth for Cloud service queries, and custom configuration files for local servers. It detects coding-agent environments and defaults to JSON on stdout, uses gh-style exit codes, reads CLICKHOUSE\_ credentials from a working-directory .env file, and hides deprecated API fields from CLI output. Cloud service queries can authenticate with OAuth without provisioning a Query Endpoint; idled services wake automatically, while stopped services fail with a start hint. For local development, selected versions resolve from installed binaries before network lookup, local use can put ClickHouse on PATH, and named XML, YAML, or YML files overlay built-in defaults. The release also adds Python installation options and extends local init with a postgres/ tree alongside clickhouse/.


[Newer posts](https://yomu.fyi/topic/postgres/page/4.md) · [Older posts](https://yomu.fyi/topic/postgres/page/6.md)