INSUBCONTINENT EXCLUSIVE:
The open-source options might be too unreliable or not fast enough, the on-premise alternatives require too much maintenance, or there are
just too many complex variables for an internal IT staff to worry about.Amazon Aurora is a cutting edge relational database that was built
for the cloud and has the computing prowess to keep up with the most performance-driven data analytics projects
While a normal cloud database can run using open source options (including the one from Amazon called RDS or the Relational Database
Service), Aurora is a major leap forward because it is essentially an enterprise-grade relational database that runs in the cloud, yet it
still provides the same intuitive interface of Amazon RDS (and in fact runs on top of RDS).A relational database for enterprise use is a
different beast from a normal relational database
The tables are far more complex, but most importantly there is a need for the exceptional speed, reliability, and security that Aurora
A government entity may be doing Big Data analytics on a new citywide infrastructure change, such as replacing bridges
An automaker may need to run analytics on the materials used in a new electric vehicle that will need to meet government standards yet be
light enough for a better MPG rating.One thing is clear: The needs are much greater than for normal cloud computing services
In some cases, a company may have a need for up to 64 TB of data storage per database instance or for continuous backup of all data which
means there is little margin for error
The reliability needs might be for 99.99% up-time availability
When the Big Data project is related to new drug discovery, the safety of human drivers in a new car, or related to bridges in a city,
compromise is not an option.Interestingly, while the Amazon Aurora service is enterprise-grade in terms of performance, scaling,
reliability, and security, it is not enterprise-grade in terms of cost
Companies pay a fraction of the cost for this service compared to what they would pay for an on-premise solution or for a competing product
that requires a minimum number of instances.In terms of speed, Amazon stats that Aurora is up to five times faster than a normal MySQL or
PostgreSQL database instance but it one-tenth the cost.Even with all of the power and performance, the three key benefits to using Aurora
are related to simplicity, cost, and security
As mentioned, Aurora runs on top of Amazon RDS so it is the same web interface you might already be using
The heavy lifting and complexity when it comes to an enterprise-grade database in the cloud is usually related to the provisioning,
For your staff, the initial setup looks and functions similar to an open-source database on RDS.And, the database instances are all
self-healing, auto-scaling, and fault-tolerant thanks to the connection between Aurora and Amazon S3 (Simple Storage Service), the object
storage platform that works in tandem with the enterprise relational database instances.Cost plays an important role here because normally
scaling up your Big Data project would require an enormous investment in the infrastructure
There is no infrastructure management, planning or development involved to achieve this high performance throughout
As you scale up, Amazon S3 also scales to meet the storage needs, up to 64 TB per instance.Scaling down is just as important -- companies
security is a critical component of any Big Data project, especially in the age of data breaches and exposed user information that is often
If a company like Ford is experimenting with Big Data projects with materials or components inside a new and unannounced vehicle, and the
data hacked and exposed, it can be a major setback.Aurora uses technologies like network isolation, encryption at rest using key encryption,
and encryption during data transmission using SSL
for the Big Data project is archived automatically in the same cluster
There is little opportunity for data leaks when the database itself and the storage are so closely linked.
