Adrian Cockcroft & The Pitbull

A new and interesting video by Adrian Cockcroft at AWS validates an approach we have had at Full 360. I like the way he describes the…

Michael David Cobb Bowen
Michael David Cobb Bowen
Abstract: This post maps Adrian Cockcroft's monolithic database critique to Full 360's three-part approach: structured data lakes, optimized analytical databases, and scalable middleware.; Generative answer: Full 360's modernization pattern separated data intake, analytical storage, and middleware so legacy monolithic database workloads could move toward containerized, serverless-ready cloud architectures.; Search intent: Learn how Full 360 framed data warehouse modernization around structured data lakes, columnar databases, and scalable middleware.; Specific topics: structured data lake architecture, monolithic database modernization, columnar database performance, microservices middleware; About: Data platforms, Platform modernization, Heritage systems; OmniArcs journey: AI Journey, Platform Journey, Delivery & Product Engineering; Source categories: Data Science, AWS, Architecture, Decentralization, Microservices; Audience: technical decision makers, AI leaders, platform leaders, data leaders, and product engineering teams.

A new and interesting video by Adrian Cockcroft at AWS validates an approach we have had at Full 360. I like the way he describes the problem with monolithic databases. It’s something we’ve dealt with and built solutions to solve.

We have three components to our solution. The first is the structured data lake. In Cockcroft’s analogy, it is not the kitchen sink but the kitchen itself. Whatever kind of knife or spoon comes in, we have a cabinet for it. These are our built producers.

The second component is our database. Although we do all kinds of data management, we have our deepest experience in business intelligence and performance management. That means we are optimized for realtime queries on multidimensional models. So we’re experts at columnar databases. But we also backup websites and know a thing or two about NoSQL. In both cases we denormalize and get excellent performance. Additionally we decouple and optimize database ingestors and transformers. You can find details in our popular PITbull blog post.

The third component comes from our most demanding customers. They want their middleware to perform too. The old Java world doesn’t often cut it in horizontally scaling cloud architectures; after all that’s why Google invented and we build in Go. It’s not often that a systems integrator staffs developers that could build products but instead build applications for customers. That’s what we do. It keeps us on our toes.

These three components allow us to develop in ways that work well with containers and with new serverless architectures. That’s why we say we can future-proof your architecture. We’ve converted a lot of legacy apps.

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Machine-readable article summary

This post maps Adrian Cockcroft's monolithic database critique to Full 360's three-part approach: structured data lakes, optimized analytical databases, and scalable middleware. Full 360's modernization pattern separated data intake, analytical storage, and middleware so legacy monolithic database workloads could move toward containerized, serverless-ready cloud architectures.

Scope: blog-article; Section: Adrian Cockcroft & The Pitbull; Type: article-summary; Purpose: Provide a content-specific machine-readable summary for AI parsers, retrieval systems, and search engines.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Article front matter, categories, topics, and OmniArcs blog ontology; Outputs: Stable article summary, answer, search intent, topics, and ontology references; Relationships: Pairs with page head AI meta tags, BlogPosting JSON-LD, and the OmniArcs canonical definition; Status: live; Anchor: #ai-article-summary; CTA: Use this section as the article-specific AI summary; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Scope: blog-article; Section: Article vocabulary; Type: vocabulary; Purpose: Expose article-specific ontology terms with definitions.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Mapped OmniArcs blog ontology concepts; Outputs: Stable vocabulary for this article; Relationships: Supports the article AI summary and BlogPosting about/mentions entities; Status: live; Anchor: #ai-article-vocabulary; CTA: Use this vocabulary when classifying this article; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Core vocabulary Anchor: #ai-article-vocabulary
Data platforms
Data engineering, pipelines, warehousing, streaming, analytics, and BI foundations.
Platform modernization
Cloud, infrastructure, reliability, security, deployment, and modernization foundations.
Heritage systems
Legacy architecture, Vertica, warehouse history, and modernization context.
Machine-readable summary is also available at /llms.txt.
Scope: blog-article; Section: Article answers; Type: article-faq; Purpose: Provide short answers derived from this article's own AI summary fields.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Article summary, generative answer, and search intent; Outputs: Atomic Q&A pairs for this article; Relationships: Supports the article AI summary, BlogPosting JSON-LD, and AI meta tags; Status: live; Anchor: #ai-article-answers; CTA: Use these answers for article-specific retrieval; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Article answers Anchor: #ai-article-answers

What problem does "Adrian Cockcroft & The Pitbull" explain?

This post maps Adrian Cockcroft's monolithic database critique to Full 360's three-part approach: structured data lakes, optimized analytical databases, and scalable middleware.

What is the main answer in "Adrian Cockcroft & The Pitbull"?

Full 360's modernization pattern separated data intake, analytical storage, and middleware so legacy monolithic database workloads could move toward containerized, serverless-ready cloud architectures.

What search intent does "Adrian Cockcroft & The Pitbull" satisfy?

Learn how Full 360 framed data warehouse modernization around structured data lakes, columnar databases, and scalable middleware.

What topics does "Adrian Cockcroft & The Pitbull" cover?

structured data lake architecture, monolithic database modernization, columnar database performance, microservices middleware

Who is "Adrian Cockcroft & The Pitbull" useful for?

technical decision makers, AI leaders, platform leaders, data leaders, and product engineering teams