Simplicity is something most of us strive for in both our personal and work lives. If you have been responsible in the past for database platforms, I doubt that you yearn for a return to the days when you had to figure out which disk spindles to put your data files on to maximize IO throughput, or figure out CPU/NUMA node affinity, or battling storage admins for more IOPs and capacity. One exception may be the highly paid rockstar consultants we paid to beat our databases into shape to shave minutes or hours off important queries without buying more database software licenses or bigger servers.
In our search for simplicity, agility, and pursuit of the cloud, we’ve veered a little too far into the agility camp and started to ignore the details of how data warehouse technologies and architecture can deliver optimal value. As a result, we’ve stopped asking vendors difficult questions and understandably those vendors haven’t always focused on efficiency, resulting in expensive solutions and costs spiraling out of control. Cloud providers, addicted to compute consumption, are just as culpable in fostering this culture.
Delivering Cost Effectively at Scale
The need for more advanced data analytics capabilities answering more questions for more people and applications than ever before is well established. To achieve that agility is of course important, but the efficiency of the database platform is essential to delivering cost-effectively at scale.
At Yellowbrick some of the smartest database minds in the world have been building our MPP database engine from scratch over the last eight years. The technology underpinning Yellowbrick Data Warehouse’s technology is highly differentiated from our competitors – we are not just delivering an MPP layer on top of someone else’s database.
Driving Costs Lower with Efficiency
We believe we have the fastest, most efficient data warehouse processing engine in the world. What’s more, we are happy to tell you how it works and how all of this translates into huge resource efficiencies, lower resource, and energy consumption, faster queries, and higher workload density – ultimately delivering more productivity and value.
The Yellowbrick Data Warehouse unlocks data for every user across the enterprise with efficiencies driving costs lower.
What Makes Yellowbrick Technically Different?
There are four primary components to the Yellowbrick database engine, all written from scratch by Yellowbrick: the Storage Engine, the Execution Engine, the Workload Manager, and the Query Compiler. In addition, Yellowbrick’s engineers have optimized the entire data path and operating system process management. We call this the Direct Data Accelerator.
Are Your Vendors Actively Helping to Maximize Efficiency?
When considering the future of an existing data warehouse or a new data analytics project, make sure to ask prospective vendors exactly what they are doing to maximize efficiency and minimize costs for you. Show an interest in what technology innovations they are bringing you under the covers and make sure you understand what makes them tick. Start to ask the hard questions. What smarts are they building into their database engine and query optimizers? How quickly are they bringing you innovation from the latest advancements in CPU or storage technology? How are they managing to answer more questions, faster without making you pay more?
Engineering Excellence
With Yellowbrick, we believe it’s our engineering excellence that makes us stand out.
All of these optimizations work silently, behind the scenes whether Yellowbrick is running in the public cloud using commodity compute and storage, or on its optimized hardware appliance, Andromeda. Nothing for you to do except sit back, relax, and enjoy watching your load performance drastically improve while your costs shrink.
Read this short overview to get more detail on how all this works and benefits your data initiatives.
For an even more detailed understanding, take a look at our Inside the Yellowbrick Data Warehouse whitepaper.
