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Are Big Data appliances worth the buck

While setting up the Big Data technical environment, one of the questions which most enterprise grapple with is whether to go for an appliance or a cluster. A Big Data appliance can be defined as an integrated system which provides a combination of hardware, software, storage and network device for enabling big data use cases. A Big Data cluster on the other hand can be defined as a combination of exclusive nodes with required hardware, big data processing software, coupled storage and can be integrated together via network devices.

While appliances are usually known to involve a large payout to the vendor, comparative studies have tried to prove that the Total Cost of Ownership (TCO) may in certain cases be less or equal to a cluster setup.  Let’s take a look at whether the appliances are worth the money spent.
- Higher initial payout - Lower initial payout – with a chance to acquire new resources as you scale out
- Standard configuration across nodes - Provision to mix and match configurations based on distinct need for name node or data nodes
- High probability of vendor lock in - More liberty in terms of switching vendors and associated software and components
- Field tested Hadoop and ecosystem projects version offered as package - Need to make difficult component choices and version compatibility tests
-Lower set up time and enablement -Higher setup time and labor effort
- Eliminates learning curve for administrators on each component -Need high comfort level and education on required components
- Could have issues in installing add on software - Flexibility in terms of installing additional software
- New hardware investment - Offers possibility of leveraging existing hardware
- Need to read the fine line in contract on software upgrade and pricing - Better control on software upgrade and pricing
- Additional scaling capabilities could lead to technical and pricing challenges - More flexibility on additional scaling capability
- Will need to stick to SQL standard offered by vendor - Can choose your own preferred SQL on Hadoop solution
- Lesser hard work required for restoration of node with common support subscription - Could involve following and coordination among multiple vendors for trouble-shooting
- May involve migration costs - May not involve any major migration cost since you could add up additional nodes on the cluster

Recommended steps to arrive at decision:
  1. Collect use cases, associated data volume and growth projections
  2. Determine the Hadoop/Big data ecosystem layers that you will invest in next 3 years.
  3. Analyze software, hardware components being offered vis-à-vis requirements as listed out in steps 1 and 2 above
  4. Perform benchmark tests (if required skills are available)
  5. Compare metrics across appliances of different vendors and cluster machines with varied configuration
  6. Arrive at qualitative and quantitative comparison across the options to help you choose a winner.


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