Discovery: The Ultimate Linux Device - The Kickfire Appliance

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and I had the pleasure of interviewing Kickfire CEO Bruce Armstrong for the May 22nd episode of to discuss the Kickfire appliance. The Kickfire appliance is a Linux-based, rack-mountable, database appliance tuned for Data Warehousing.

Here's the real scoop: Starting at a mere $32,000 US, you get the horsepower performance of a system (actually a set of systems) costing in the $400,000 range. And it consumes very little power while saving you a bundle of cash while performing like big iron.

How do they do it?

Linux, MySQL Enterprise DB and a SQL chip. Read all about it .

So, now you're asking (like we did), "What about your future as an Oracle competitor now that Oracle owns MySQL?"

Armstrong stated that they (Kickfire) have discussed this change among themselves and with , creator of MySQL, about his new project the Open Database Alliance (fka MariaDB). As Armstrong sees it, Kickfire has options--lots of options and all of them smell like success. To get all the information about Kickfire's options, listen to the live .

The Kickfire appliance is an amazing machine that deserves a look if you're into data warehousing or need super speed for your queries of any kind. Remember this: 10% of the price, 10% of the power consumption, 100% of the performance of any other data warehousing solution.

That's the ultimate Linux device for which we've been searching. Innovative, creative, inexpensive, powerful. I just don't know if it gets any better than that.

Oh, wait, it just did.

Kickfire is having a where you can win a Kickfire appliance. You'll have to compete with me, of course, and others who want to win the ultimate Linux device but we'll all have fun doing it.

What do you think of the Kickfire appliance? Also let me know if you're going to enter the contest.

Dani AI

Generated

Nice find . Appliances that pair tuned software with purpose-built hardware can be a big win for analytic workloads, but they come with trade-offs. Below is a short, practical checklist and a lightweight benchmarking plan to help decide whether an appliance suits a given environment.

  • Workload fit: capture the heaviest real queries and classify them (large scans/aggregates vs small transactional ops). Appliances tend to favor analytic, scan-heavy patterns.
  • SQL compatibility: test stored procedures, user-defined functions, specific data types and any vendor SQL extensions you rely on. Run a handful of production queries end-to-end and compare results.
  • Data movement & ETL: verify bulk-load throughput, change-data-capture or replication paths, partition handling, and how your ETL tools integrate.
  • Backup, HA and restores: require documented restore procedures, snapshot/PITR options, and a failover demo under realistic load.
  • Operations & monitoring: confirm who patches OS/firmware, how logs and metrics are exposed, remote-support access, and whether the appliance fits your existing monitoring/alerting stack.
  • Exit plan: ensure you can export raw data and metadata so you can rebuild off-appliance if needed.

Benchmarking plan (practical steps)

  1. Define a representative dataset and the top 10–20 heavy queries.
  2. Record a baseline on current infra with caches cold and warm.
  3. Run repeated trials on the appliance, collecting query latency plus system counters (CPU, IO, network).
  4. Capture and compare explain plans to see what work is pushed to the device versus executed locally — that informs tuning.

If you try a demo or a promotional unit, require a proof-of-concept using your own data, success metrics, and an operational runbook. Appliances can be transformative, but the real question is how they behave on your workload and in your day-to-day operations.

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