Ian Murphy brings us this weeks Cloud Acronyms: BDaaS, HDaaS and BaaS.
BDaaS Big Data as a Service
This is an emerging term that is still not tied down to a single definition. In its broadest sense it is the supply of a set of cloud-based tools that make it possible for companies to capture, integrate, analyse and store large sets of data. Depending on the vendor delivering the service it may also include access to a range of data sources with a query engine so that the company can select a customised data set or sets to work with.
For example, there are several companies that provide access to open data from the UK and US governments. There are other companies that aggregate social media content from Twitter, Facebook, Tencent Weibo, Tumblr, bitly, Yammer and several other sources. Customers create a query against the different data sources, bring that data into a new system and then combine the various data sets with their own corporate data to find new sources of insight.
HDaaS HaDoop as a Service
There are a lot of companies that are now providing Hadoop as a Service. At one end of the scale is the most basic DIY Hadoop environment. Here the customer assembles the virtual machines, prepares the data, initialises a Hadoop environment and then runs it on the cloud service with limited support and very low pricing. At the other end of the scale there are full service environments where the customer simply needs to provide the data and the configuration, important, design and running of the DaaS is done by the service provider. All the customer needs are queries to run against the data.
BaaS Backend as a Service
Backend as a Service is designed to enable mobile developers to easily connect their applications to cloud storage and services. The developers get a common interface making it possible to do simple integration across a range of applications using the same tools. There are APIs and SDKs that make it easy to integrate the applications to the BaaS.