The Impact of The Internet of Things (IOT)

On Databases

The Stuff CIO’s and DBA’s should prepare for

Mordechai Danielov

bitwiseMnm.com

“The Internet of Things will augment your brain”

Eric Schmidt

"The Internet of Things is reaching a tipping point that will make it a sustainable paradigm for practical applications." Massimiliano Claps, research director, IDC EMEA Government Insights

In 2008, the number of devices on the Internet already exceeded the number of people. By 2020, it will reach 50 billion devices.

Home Appliances Traffic & Location

Smart Cars & Transportation

Weather & Environment

Communication Devices

Security & Surveillance

Health Monitoring & Devices

Office Appliances

Fun and Gaming

Today, IT is dependent on data created by people.

With IoT, computers will gather data independently of humans and track and count

everything.

The next generation of Internet applications using (IPv6) will communicate with devices attached to virtually all human-made objects enabled by the extremely large address space of the IPv6 protocol.

Big Data DB

Cloud Servers

Devices & “Things”

Technologies that make IoT Possible

Sensors(like RFID, pressure etc)Send out information

Applications analyze and send instructions back to devices

With IoT, “Big Data”

will turn to “Huge Data”

IDC projects that the digital universe will reach 40 zettabytes

40 ZB is equivalent to 57 times the amount of all the grains of sand on all the beaches on earth.

http://www.digitalnewsasia.com/digital-economy/massive-amounts-of-data-but-only-05percent-being-analyzed#sthash.1W4wJcp9.dpuf

Processing Power

Even if only a fraction of all of the huge data will need to be processed, that’s a lot of processing power that will need to be available for organizations.

Decoding the data generated by the Human Genome took 10 years. Today, it would take less than 1 week.

http://wikibon.org/blog/big-data-statistics/

Peaks and ValleysTransaction Rate Fluctuations can create inadvertent DoS situations

Scenarios:An alarm company hooked up to many home devices may get “sensory overload” during an earthquake from multiple endpoints.

Servers and Databases will get a high volume surge of data that requires speedy processing.

When Scaling up is just not Good Enough

Scale Out Your Resources -Smart distribution of read/write activity -Design smart: writing hubs and reading spokes-Spread out your databases and replicate

Read Only DB

Replicatio

n

Know Thy Peak

30%-70% rule

Utilize no more than 30% of your resources in “off-peak” time and reserve 70% for peaks.

70%

30%

Distribute, Cache and Share Nothing

Sharing is caring? Not with data Data must be available everywhere in the world and fast -- highly distributed databases with local application caching.The most popular approach is to build loosely connected "shared nothing" instances of databases that can be brought online in no time.

Shared Nothing

Shared Everything

Master the Cloud

It’s all about the Money

Use Cloud computing to get a handle on your cost of computing. Instead of saving 70% of capacity for peak traffic, procure it on demand with Cloud based databases and smart load balancing middle tier. Master working with cloud vendors and remote utilities.

Fully distributed

files?

Parallel ProcessingAdaptive ArchitectureData Compression

Learn from the Big Guys

Facebook DB Architecture

http://www.flickr.com/photos/ikhnaton2/533233247/

Google BigTable

"It is not a relational database and can be better defined as a sparse, distributed multi-dimensional sorted map" 

http://en.wikipedia.org/wiki/BigTable

Data Must Be Available Under Adverse Conditions

•Redundant data pathways•Smart middle layer•Fully meshed topology

Distributed data is more exposed yet

Data Must Be Secured

•Encrypt anything you can•Automate Certificate management•Know how to secure data in and out of the cloud and in between•Distribute “meaningless” data and assemble it as needed

Data Must Not be Lost

• Smart transaction control built into the data access tier •Make sure you can get data out of local cache if something goes wrong•Watch data replication latency. Make sure everyone is comfortable with it and that it doesn’t deteriorate. •Set up alerts so that you detect a problem before it’s too late.

Automate Everything

source control

deployment automation

scriptin

g

Automation for Input Management

When the peak traffic comes rushing at you, it's not the time to think. Have everything automated and scripted so that capacity can be added with a click of a button.

Want to Talk Databases?Contact us with your ideas and

suggestions

Mordechai Danielov

www.bitwiseMnm.com