Challenges and Opportunities of The Internet of Things. Interview with Steve Cellini

“The question of ‘who owns the data’ will undoubtedly add requirements on the underlying service architecture and database, such as the ability to add meta-data relationships representing the provenance or ownership of specific device data.”–Steve Cellini

I have interviewed Steve Cellini, Vice President of Product Management at NuoDB. We covered the challenges and opportunities of The Internet of Things, seen from the perspective of a database vendor.

RVZ

Q1. What are in your opinion the main Challenges and Opportunities of The Internet of Things (IoT) seen from the perspective of a database vendor?

Steve Cellini: Great question. With the popularity of Internet of Things, companies have to deal with various requirements, including data confidentiality and authentication, access control within the IoT network, privacy and trust among users and devices, and the enforcement of security and privacy policies. Traditional security counter-measures cannot be directly applied to IoT technologies due to the different standards and communication stacks involved. Moreover, the high number of interconnected devices leads to scalability issues; therefore a flexible infrastructure is needed to be able to deal with security threats in such a dynamic environment.

If you think about IoT from a data perspective, you’d see these characteristics:
• Distributed: lots of data sources, and consumers of workloads over that data are cross-country, cross-region and worldwide.
• Dynamic: data sources come and go, data rates may fluctuate as sets of data are added, dropped or moved into a locality. Workloads may also fluctuate.
• Diverse: data arrives from different kinds of sources
• Immediate: some workloads, such as monitoring, alerting, exception handling require near-real-time access to data for analytics. Especially if you want to spot trends before they become problems, or identify outliers by comparison to current norms or for a real-time dashboard.
These issues represent opportunities for the next generation of databases. For instance, the need for immediacy turns into a strong HTAP (Hybrid Transactional and Analytic Processing) requirement to support that as well as the real-time consumption of the raw data from all the devices.

Q2. Among the key challenge areas for IoT are Security, Trust and Privacy. What is your take on this?

Steve Cellini: IoT scenarios often involve human activities, such as tracking utility usage in a home or recording motion received from security cameras. The data from a single device may be by itself innocuous, but when the data from a variety of devices is combined and integrated, the result may be a fairly complete and revealing view of one’s activities, and may not be anonymous.

With this in mind, the associated data can be thought of as “valuable” or “sensitive” data, with attendant requirements on the underlying database, not dissimilar from, say, the kinds of protections you’d apply to financial data — such as authentication, authorization, logging or encryption.

Additionally, data sovereignty or residency regulations may also require that IoT data for a given class of users be stored in a specific region only, even as workloads that consume that data might be located elsewhere, or may in fact roam in other regions.

There may be other requirements, such as the need to be able to track and audit intermediate handlers of the data, including IoT hubs or gateways, given the increasing trend to closely integrate a device with a specific cloud service provider, which intermediates general access to the device. Also, the question of ‘who owns the data’ will undoubtedly add requirements on the underlying service architecture and database, such as the ability to add meta-data relationships representing the provenance or ownership of specific device data.

Q3. What are the main technical challenges to keep in mind while selecting a database for today’s mobile environment?

Steve Cellini: Mobile users represent sources of data and transactions that move around, imposing additional requirements on the underlying service architecture. One obvious requirement is to enable low-latency access to a fully active, consistent, and up-to-date view of the database, for both mobile apps and their users, and for backend workloads, regardless of where users happen to be located. These two goals may conflict if the underlying database system is locked to a single region, or if it’s replicated and does not support write access in all regions.

It can also get interesting when you take into account the growing body of data sovereignty or residency regulations. Even as your users are traveling globally, how do you ensure that their data-at-rest is being stored in only their home region?

If you can’t achieve these goals without a lot of special-case coding in the application, you are going to have a very complex, error-prone application and service architecture.

Q4. You define NuoDB as a scale-out SQL database for global operations. Could you elaborate on the key features of NuoDB?

Steve Cellini: NuoDB offers several key value propositions to customers: the ability to geo-distribute a single logical database across multiple data centers or regions, arbitrary levels of continuous availability and storage redundancy, elastic horizontal scale out/in on commodity hardware, automation, ease and efficiency of multi-tenancy.
All of these capabilities enable operations to cope flexibly, efficiently and economically as the workload rises and dips around the business lifecycle, or expands with new business requirements.

Q5. What are the typical customer demands that you are responding to?

Steve Cellini: NuoDB is the database for today’s on-demand economy. Businesses have to respond to their customers who demand immediate response and expect a consistent view of their data, whether it be their bank account or e-commerce apps — no matter where they are located. Therefore, businesses are looking to move their key applications to the cloud and ensure data consistency – and that’s what is driving the demand for our geo-distributed SQL database.

Q6. Who needs a geo-distributed database? Could you give some example of relevant use cases?

Steve Cellini: A lot of our customers come to us precisely for our geo distributed capability – by which I mean our ability to run a single unified database spread across multiple locations, accessible for querying and updating equally in all those locations. This is important where applications have mobile users, switching the location they connect to. That happens a lot in the telecommuting industry. Or they’re operating ‘follow the sun’ services where a user might need to access any data from anywhere that’s a pattern with global financial services customers. Or just so they can offer the same low-latency service everywhere. That’s what we call “local everywhere”, which means you don’t see increasing delays, if you are traveling further from the central database.

Q7. You performed recently some tests using the DBT2 Benchmark. Why are you using the DBT2 Benchmark and what are the results you obtained so far?

Steve Cellini: The DBT2 (TPC/C) benchmark is a good test for an operational database, because it simulates a real-world transactional workload.
Our focus on DBT2 hasn’t been on achieving a new record for absolute NOTPM rates, but rather to explore one of our core value propositions — horizontal scale out on commodity hardware. We recently passed the 1 million NOTPM mark on a cluster of 50 low-cost machines and we are very excited about it.

Q8. How is your offering in the area of automation, resiliency, and disaster recovery different (or comparable) with some of the other database competitors?

Steve Cellini: We’ve heard from customers who need to move beyond the complexity, pain and cost of their disaster recovery operations, such as expanding from a typical two data center replication operation to three or more data centers, or addressing lags in updates to the replica, or moving to active/active.

With NuoDB, you use our automation capability to dynamically expand the number of hosts and regions a database operates in, without any interruption of service. You can dial in the level of compute and storage redundancy required and there is no single point of failure in a production NuoDB configuration. And you can update in every location – which may be more than two, if that’s what you need.

———————–
Steve Cellini VP, Product Management, NuoDB
Steve joined NuoDB in 2014 and is responsible for Product Management and Product Support, as well as helping with strategic partnerships.

Steve holds a Sc.B in Engineering Physics from Cornell University.

Resources

– DBT-2 Clone from SourceForge

– Setting up DBT-2 for NuoDB, Github

– One Million NOTPM DBT2 Benchmark on NuoDB 2.3 By Dai Klegg, NuoDB, Sr Director of Product Marketing. ODBMS.org

– Hybrid Transaction and Analytical Processing with NuoDB. Technical Whitepaper, NuoDB. ODBMS.org

Related Posts

– Big Data, Analytics, and the Internet of Things. Mohak Shah, analytics leader and research scientist at Bosch Research, USA, ODBMS.org

– SMART DATA: Running the Internet of Things as a Citizen Web. by Dirk Helbing , ETH Zurich. ODBMS.org

– On Big Data and the Internet of Things. Interview with Bill Franks. ODBMS Industry Watch, March 9, 2015

Follow ODBMS.org on Twitter: @odbmsorg

##