A number of providers with very different requirements, licenses and subscriptions are involved in many big data analytics environments. The terms that these software vendors offer may be influenced by the infrastructure and user structures alike. It is important both before and during the project to keep a keen eye on the costs, possible risks, license management and the functionalities that the various options entail. This helps ensure that big data analytics projects proceed within a calculable and predictable framework.
A large number of companies are already working flat out to test new and innovative software solutions. Naturally, test projects that deliver particularly good results with Hadoop or another analytic (search) tool are taken to be especially meaningful. Brought together with existing data sources, the projects become part of the production environment. In many cases, though, departments and administrations are not always clear about how to use big data analytics software. After all, in many cases the solutions were created on a laptop by a development or web team working at a remote location. Therefore, not all Hadoop distributions are adequately protected against unwanted access when used straight out-of-the-box. This may expose companies to substantial, even financial risks. License or subscription fees can also add up, also with potential consequences for the future.
Strong support is available for the most familiar solutions like Apache Solr, Spark, Elastic and Splunk. Users are asked only to sign up for subscriptions, which – like licenses – come with a variety of price and support levels. There is also a number of public support forums, some of them providing 24/7 assistance and fast response times. The prices and levels on offer from the most popular providers also differ. It is therefore advisable to take a good look at the specific properties of the different big data analytics products at an early stage. This way the users can make quick and nevertheless sustainable decisions when the time comes.