HBase vs IBM Cloudant

• Scalability. HBase can scale to trillions of records.
• Fast. HBase is extremely fast to scan values or retrieve individual records by key.
• HBase can be accessed by standard SQL via Apache Phoenix.
• Integrated. I can easily store and retrieve data from HBase using Apache Spark.
• It is easy to set up DR and backups.
• Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.

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• For us, performance and scalability is the key, and Cloudant DB backed by CouchDB is scalable and performant.
• IBM Cloudant dB is very easy to provision for sandbox, development, QA as well as production.
• Support for Java for CouchDB app server analytics enables a greater control for over developers.
• Schema free oriented very easy to program and build applications on it.
• We love it!!

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• There are very few commands in HBase.
• Stored procedures functionality is not available so it should be implemented.
• HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory. HBase integrated with Map-reduce jobs will result in random latencies.

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• It was only after we went with the cloud-based solution that IBM rolled out an on-premise version.
• We found that a 3rd-party ODBC driver was required for a few applications that needed to pull data out of Cloudant.
• The sales process was difficult because the salesperson we used was not as versed on Cloudant as I had hoped.

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• As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
• Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
• The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.

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• Saving in-terms of cost of procuring and maintaining hardware, which will be realized over the next 5 years.
• Positive ROI in terms of the number of FTEs involved in maintaining our databases; our DBAs can now focus on other important and business critical applications.
• Best ROI in terms of our organization's vision - they are no longer anxious / nervous to move to the cloud. We are already on the CLOUD.

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