Robin Schumacher

Excited to be at DataStax!

By Robin SchumacherJuly 25, 2011

Hello to all of you around the globe who use Cassandra! My name is Robin Schumacher and I’ve just joined DataStax as VP of Products. I’m excited to be a part of the great team here at DataStax, and I look forward to interacting with many of you through this blog, at Cassandra/NoSQL/Big Data user groups and events, and one-on-one meetings.

As someone who’s been a database guy from literally Day 1 of my career in information technology, I’m not sure there’s been a more exciting time to be involved in data management. Unless you’ve been under a rock somewhere, you know that data – and more correctly, information – has become perhaps the most strategic asset of today’s modern business. It doesn’t matter whether you’re a spare-bedroom-based shoestring startup or a monolithic, multi-billion dollar corporation, the acquisition, storage, manipulation, and distribution of information throughout your organization will make or break how well you compete in your chosen arena.

I’ve been lucky to work in the field with most every RDBMS around. I’ve had the opportunity to start and run the product management group at a major database tools company and design software that manages, monitors, and tunes databases on many different platforms (e.g. Oracle, SQL Server, etc.) I was privileged to start and run the product management team at MySQL and be a part of the great things that happened there both before and after the acquisition by Sun (and then by Oracle). And most recently, I was fortunate to work with the staff at EnterpriseDB to create/design new products that will help make PostgreSQL even better than it already is.

During my time at these companies, I’ve had the pleasure of working with many different customers across a wide variety of industries. And I’ve been amazed at the efforts of the data management teams at these organizations, and the heavy duty, data-driven systems they’ve developed and maintained.

But in the past year, I’ve noticed something happening at literally every customer I’ve visited. Every one of them is implementing a NoSQL strategy.

Every one.

And these are places that don’t add new data platforms flippantly. They only do so when they have a true need with real business problems that need solving, AND they can’t crack the nut the needs cracking with their current database software.

As I’ve made my rounds with these companies, I’ve noted that while the specific issues facing them differ, there are three core areas that they’re all looking to address with a move to NoSQL solutions.

First, is the big data issue. If there’s one statement I’ve heard time andagain from these successful businesses, it’s “I never thought we’d grow this fast!” Collecting, managing, and analyzing all the data coming into these organizations is a major challenge, and it’s only getting more widespread and common.

Industry analysts like IDC will tell you that most (85%+) “big data” implementations are under 5 or so terabytes, but that’s not the whole story. The fact is, such a limitation is artificial in that it’s not what these companies want to do, but it’s what their current database software (and/or their IT budgets) constrains them to do. If the truth be told, these companies want to analyze much more data than they can now.

The second major issue I’ve seen at successful businesses is their need for a much improved distributed database framework. You’d think after all these years that RDBMS replication methods would have kept up with the need for distributed data, but that hasn’t happened at all.

The companies I’ve talked to are tired of manually sharding their systems, exhausted at the inflexibility and problematic nature of master-slave implementations, and fed up with high-priced and consultant-architected database systems that promise fewer headaches and more uptime, but instead deliver splitting migraines and costly downtime.

Instead, what they want is an easy to setup, reliable,flexible, highly available, fault tolerant, write-anywhere, read-anywhere, load-balanced distributed database architecture that can span data centers and geographies with ease. Oh, and also add and subtract nodes when desired with no impact on uptime.

And make no mistake – this need isn’t just for big data players; small to medium systems many times have the exact same set of distributed database requirements.

The third and last thing I’ve encountered is a desire to move to a more flexible data model than what than what Codd and Date have given us. Make no mistake, the relational model is good for many types of applications, but today’s modern business has a different set of requirements for the data it needs to turn into information for analysis. And these requirements dictate a new way of modeling and designing both structured and unstructured data so that the right decisions can be made at companies by those calling the shots.

This is why I’m so excited to be at DataStax. These three issues: the big data problem, the need for a better distributed database framework, and the desire for a new data model, are all being addressed and handled here in one of the most elegant fashions I’ve seen.

It’s a privilege for me to have the opportunity to work with both the talented engineers here at DataStax and those in the Cassandra community. They’re solving some of the toughest problems that face data professionals today, and I can tell you that there are some exciting things in development now that will wow you when they’re released.

I’m looking forward to talking and working with all of you to create a data platform that gets and keeps your trust and is up to the challenge of handling pretty much whatever you want to throw at it. I’ll also do my best to keep you up to date on what’s coming down the pike and ensure that your feedback and requests make it into our product roadmaps here at DataStax so that we’re delivering exactly what you need.

Please contact me anytime you have questions, input, or anything else you want to pass along to us here at the company. You can reach me at

Thanks for your support of Cassandra and DataStax!



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