--- title: "Lakehouse" description: "46 posts about Lakehouse, summarised, each linking to the original." --- # Lakehouse > 46 posts about Lakehouse, summarised, each linking to the original. ## Articles ### [Concurrency Control in DBMS: How Locking, MVCC and Optimistic Strategies Keep Data Consistent](https://yomu.fyi/post/concurrency-control-in-dbms-how-locking-mvcc-and-optimistic-strategies.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Databricks Staff - Published: Apr 21, 2026 The guide explains how database management systems coordinate simultaneous transactions to preserve consistency and serializability, preventing dirty reads, lost updates, non-repeatable reads and phantom reads. It compares lock-based control, including shared and exclusive locks and two-phase locking, with MVCC, which gives transactions consistent snapshots and lets readers and writers proceed without blocking. The discussion covers pessimistic and optimistic strategies, isolation levels, deadlocks, retries, lock-granularity trade-offs and MVCC’s storage and garbage-collection costs, including PostgreSQL’s VACUUM. For lakehouse workloads, Delta Lake uses a read-validate-commit process with optimistic concurrency, snapshot isolation and conflict detection for concurrent writes. The source presents Databricks Lakebase as a managed implementation offering optimistic concurrency control, snapshot isolation for reads and write-serializable isolation for writes without lock or deadlock management. ### [Bridging data science and marketing: Databricks unveils Delta Sharing integration for Adobe Experience Platform and agentic marketing workflows](https://yomu.fyi/post/bridging-data-science-and-marketing-databricks-unveils-delta-sharing-i.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Justin Fenton, Dan Zuckerberg, Katy Yuan - Published: Apr 20, 2026 Databricks and Adobe announce three partnership milestones aimed at connecting governed Lakehouse data with marketing activation in Adobe Experience Platform. The changes include Delta Sharing support for zero-copy access, a Databricks Genie connection to Adobe Marketing Agent through Model Context Protocol (MCP), and an upcoming Adobe Marketing Agent beta for the Databricks Marketplace. Using Unity Catalog as the source, Experience Platform can access shared tables and views as virtual tables, while Adobe Data Distiller queries live Databricks data without copying underlying records. Through MCP, agents in both platforms can use governed datasets, metadata, models, campaign metrics, SQL Warehouses, and Model Serving endpoints with natural-language interactions. The stated outcome is a shared, real-time context for audience creation, campaign analysis, closed-loop attribution, and model improvement, while reducing data movement, duplication, latency, egress, and governance overhead. ### [Governing coding agent sprawl with Unity AI Gateway](https://yomu.fyi/post/governing-coding-agent-sprawl-with-unity-ai-gateway.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Aarushi Shah, Ankit Mathur, Bilal, Kevin Stumpf, Rohit Agrawal, Harish Gaur, Ana Nieto - Published: Apr 17, 2026 Databricks introduces coding agent support in Unity AI Gateway to address security, cost, and visibility challenges created by organizations using multiple coding tools. The gateway provides a unified governance hub for Codex, Cursor, and Gemini CLI, combining access controls, usage statistics, operational observability, cost management, guardrails, and inference capacity. Agent access can be governed centrally, with audit logs in Unity Catalog, MCP servers managed in Databricks, MLflow tracing, shared cost limits, and coding metrics and traces ingested into Unity Catalog-managed Delta tables through OpenTelemetry. The announcement says developers can authenticate with Databricks credentials across connected services, use centralized budgets and model capacity, and let organizations analyze adoption, developer velocity, and rate-limit pressure in the lakehouse; support for Cursor, Gemini CLI, and Codex CLI is available to all Databricks customers. ### [Banks don't have an AI problem — they have a data platform problem](https://yomu.fyi/post/banks-don-t-have-an-ai-problem-they-have-a-data-platform-problem.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Naeem Rehman, Jennifer Miller - Published: Apr 17, 2026 The post argues that banks’ difficulty scaling AI stems less from model capability than from fragmented data, weak governance, and limited real-time access. Examples from CBA Live 2026 include model drift in credit scoring, fragmented customer signals, and a collections model that predicted, with 85% accuracy, how many days newly delinquent accounts would take to cure using governed data. It also presents Erica’s 3.2 billion interactions since 2018 as evidence that production AI requires continuous tuning, monitoring, and edge-case management, while generic models decay in frontline settings. The proposed Databricks architecture combines Lakehouse, Unity Catalog, Lakeflow, Lakebase, MLflow, Model Monitoring, Online Feature Store, Genie, and Agent Bricks to support governed analytics, low-latency decisions, auditable models, and constrained agent actions. Its conclusion is that a shared data platform should precede additional AI use cases because it improves deployment speed, trust, explainability, and regulatory defensibility. ### [Open Platform, Unified Pipelines: Why dbt on Databricks is Accelerating](https://yomu.fyi/post/open-platform-unified-pipelines-why-dbt-on-databricks-is-accelerating.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Srilekha Dornadula, Ramiz Bozai - Published: Apr 16, 2026 dbt provides structure for transforming raw data into curated datasets, but the post argues that its effectiveness depends on the underlying platform. Databricks is presented as an open lakehouse combining storage, compute, governance, orchestration, and monitoring to reduce duplicated data, fragmented permissions, and operational overhead. Lakeflow Jobs runs dbt alongside ingestion, downstream actions, retries, and dependencies, while Unity Catalog supplies persistent permissions, documentation, lineage, and fine-grained controls. The integration also supports Delta Lake and Apache Iceberg, query tags for cost tracking, Photon, Predictive Optimization, Liquid Clustering, and dbt materialized views. The post concludes these capabilities provide openness, integrated operations, governance, and price-performance for dbt workflows, citing one customer’s consolidation of notebooks and 7+ source systems and more than 2,900 customers already running dbt on Databricks. ### [8 AI and data trends shaping financial services in 2026](https://yomu.fyi/post/8-ai-and-data-trends-shaping-financial-services-in-2026.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Kim Hatton, Junta Nakai, Marcela Granados, Antoine Amend, Ashraf Safdar, Jennifer Miller, Andrea DeSosa, Rajaram Suresh - Published: Apr 14, 2026 The post argues that financial-services AI adoption is widespread, but execution—not model capability or strategy—is determining who captures value in 2026. It attributes stalled pilots to fragmented legacy infrastructure, inconsistent data, weak lineage, and insufficient control for governed, real-time workflows such as fraud detection, pricing, and personalization. Firms advancing further treat data as a managed asset, embed governance in data and model pipelines, and align data, analytics, and AI teams around shared definitions, workflows, and metrics. The proposed remedy is a unified lakehouse environment combining storage, compute, governance, lifecycle management, orchestration, streaming, and AI workflows, with Unity Catalog providing centralized access control, lineage, and auditing. The conclusion is that by the end of 2026, firms that embed AI into operational decisioning at scale will pull ahead of organizations still running pilots. [Newer posts](https://yomu.fyi/topic/lakehouse/page/2.md)