Deploy, Score, and Compare Data Infrastructure on K8s with Lakebench

In the Lab / /

Finding which lakehouse architecture performs best on your infrastructure is expensive. Deploying a single stack on Kubernetes by hand takes days (ask me how I know). A different catalog, a different query engine, a different version, different resource profiles. The cost of the first deployment is high. The cost of repeating it for every permutation […]

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Data Architectures and Their Economics

On Markets / /

Part 1 of The Economics of Data Architectures in 2026 The Modern Data Stack is Dead The Modern Data Stack (MDS) was never an architecture. It was a philosophy: best-of-breed tools, loosely coupled via APIs, separation of concerns. Fivetran for ingestion. Snowflake for storage. dbt for transformation. Looker for visualization. Buy the pieces, assemble yourself.

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Installing Oracle Database 19c RAC on OEL 8: Four Traps

In the Lab / /

I recently built a two-node Oracle RAC 19c cluster on Oracle Linux 8.10 with Pure Storage FlashArray backend. The hardware was solid, the network was configured, the storage was presented. What should have been a straightforward installation turned into a four-hour troubleshooting session because of issues that aren’t documented in Oracle’s installation guides. This post

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Demystifying the Analytics Market in 2025

On Markets / /

This is the third in my series analyzing data-centric markets. See also: Demystifying the Database Market in 2025 and Demystifying the Data Governance Market in 2025. It’s interesting how major vendors position themselves now, none of them lead with “analytics”. Databricks calls itself “the Data and AI company.” Snowflake is “the AI Data Cloud.” dbt

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Oracle Database Support for HammerDB-Scale

In the Lab / /

Oracle ranks #1 on the DB-Engines database popularity ranking, ahead of MySQL, SQL Server, and PostgreSQL. Running Oracle benchmarks alongside SQL Server in my day-to-day testing made perfect sense from the start, but HammerDB-Scale v1.0 focused on getting SQL Server working properly first. Version 1.1 adds Oracle support with the same parallel orchestration framework that

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Schrödinger’s dNFS: The Empty Row Mystery

In the Lab / /

You will end up here: v$dnfs_servers returns no rows. You’ve checked everything. The library is linked. The alert log shows dNFS loaded. Your oranfstab is syntactically perfect. The NFS mounts are there. And you’re convinced it’s broken, I was too. I spent three hours proving dNFS was configured correctly while simultaneously proving it wasn’t working.

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Stress Testing Consolidated Platforms with Database Workloads

In the Lab / /

Your storage vendor claims 500K IOPS. Your server vendor promises 128 cores of “enterprise-grade performance.” Your hypervisor can “easily handle” 50 VMs. Your network fabric has “plenty of headroom.” Then you consolidate eight production databases onto the platform and everything falls over at 3 AM on a Tuesday. What happened? Nobody actually tested what happens

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Evaluating Storage Read Cache for Different Database Designs

In the Lab / /

This blog post is focused on the different datasets I have designed to evaluate Pure Storage® DirectMemory Cache with various databases like SAP HANA, MySQL and MariaDB. More information on the results can be found in the blog posts Reducing costs for SAP HANA with Pure’s DirectMemory Cache and Accelerate MySQL Read Scale with DirectMemory

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MySQL Backup and Recovery

In the Lab / /

There are a number of ways in which data protection/data mobility can be done with MySQL. The documentation splits backups into two categories. Physical Backups – Raw copies of directories and files which store database contents Logical backups – Logical backups save information in the form of reproducing the database object structure  to the point

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