When Kappa first appeared as an architecture style (introduced by Jay Kreps) I was really fond of this new approach.
One of my 5 predictions for 2019 is about Hadoop. Basically, I do expect that a lot of projects won’t take Hadoop as a full-blown solution anymore. Why is that? Basically, one of the most exciting news in 2018 was the merger between Hortonworks and Cloudera. The two main competitors now joining forces? How can this happen? Basically, I do believe that a lot of that didn’t come out of a strength of the two and that they somehow started to “love” each other but rather out of economical calculations. Now, it isn’t a competition between Hortonworks or Cloudera anymore (even before the merger), it is rather Hadoop vs. new solutions. These solutions are highly diversified – Apache Spark is one of the top competitors to it. But there are also other platforms such as Apache Kafka and some NoSQL databases such as MongoDB, plus TensorFlow emerging. One would now argue that all of that is included in a Cloudera
Another year has passed and 2018 has been a really great year for the cloud. We can now really say that cloud is becoming a commodity and common sense. After years of arguing why the cloud is useful, this discussion is now gone. Nobody doubts the benefits of the cloud anymore. The next year, most developments that already started in 2018 will continue and intensify. My predictions for 2019 won’t be revolutionary but the trends we will see in the short period of this year. Therefore, my 5 predictions for 2019 are: 1. Strong growth in the cloud will continue, but it won’t be hyper growth anymore In the past years, companies such as Amazon or Microsoft saw significant growth rates in their cloud business. These numbers will still go up by a large, double digit, growth rate for all major cloud providers (not just the two of them). However, overall growth will be slower than previous years as the
Now you probably think: is Mario crazy? In fact, during this post, I will explain why cloud is not the future. First, let’s have a look at the economic facts of the cloud. If we look at share prices of companies providing cloud services, it is rather easy to say: those shares are skyrocketing! (Not mentioning recent drops in some shares, but these are rather market dynamics than real valuations). One thing is also about overall company performances: the income of companies providing cloud services increased a lot. Have a look at the major cloud providers such as AWS, Google, Oracle or Microsoft: they make quite a lot of their revenue now with cloud services. So, obviously here, my initial statement seems to be wrong. So why did I just choose this one? Still crazy? Let’s look at another explanation on this: it might be all about technology, right? I was recently playing with AWS API Gateway and AWS Lambda.
As 2016 is around the corner, the question is what this year will bring for Big Data. Here are my top assumptions for the year to come: The growth for relational databases will slow down, as more companies will evaluate Hadoop as an alternative to classic rdbms The Hadoop stack will get more complicated, as more and more projects are added. It will almost take a team to understand what each of these projects does Spark will lead the market for handling data. It will change the entire ecosystem again. Cloud vendors will add more and more capability to their solutions to deal with the increasing demand for workloads in the cloud We will see a dramatic increase of successful use-cases with Hadoop, as the first projects come to a successful end What do you think about my predictions? Do you agree or disagree?
2016 is around the corner and the question is, what the next year might bring. I’ve added my top 5 predictions that could become relevant for 2016: The Cloud war will intensify. Amazon and Azure will lead the space, followed (with quite some distance) by IBM. Google and Oracle will stay far behind the leading 2+1 Cloud providers. Both Microsoft and Amazon will see significant growth, with Microsoft’s growth being higher, meaning that Microsoft will continue to catch up with Amazon More PaaS Solutions will arrive. All major vendors will provide PaaS solutions on their platform for different use-cases (e.g. Internet of Things). These Solutions will become more industry-specific (e.g. a Solution specific for manufacturing workflows, …) Vendors currently not using the cloud will see declines in their income, as more and more companies move to the cloud Cloud Data Centers will become more often outsourced from the leading providers to local companies, in order to overcome local legislation Big
On top of all those collaboration- and cloud-services a lot of us have found out that working together has not become much easier since the introduction of those services. As today every organization uses own infrastructure either self-hosted or an online services the borders have only moved but have not gotten transparent when needed. The walls between collaborating organisations are as strong as ever. SPHARES is here to change this. We are allowing sharinglike DropBox, but between different systems. Even hosted on your own systems -Dietmar Gombotz, CEO of SPHARES SPHARES is a small start-up team of 5 from Vienna with the mission to make working-life and collaboration much easier by providing a tool that allows you to integrate different work environments without having to actually change tools. It is working as a service-integrator between different systems in the background. The sync-engine allows to transparently share data to and from colleagues using different (or even the same) systems as oneself.
Self-driving cars are getting more and more momentum. In 2014, Tesla introduced the “Autopilot” feature for it’s Model S, which allows autonomous driving. The technology for self-driving cars has been around for years though – there are other factors why it is still not here. It is mainly a legal question and not a technical one. However, autonomous systems will be here in some years from now, and they will have a positive impact on cloud computing and big data. The use-cases were already described partially with smart cities in an earlier post. However, there are several other use-cases. Positive effects of self-driving cars are the advanced security: sensors need milliseconds to react to threads whereas humans need a second. This gives more time for better reactions. Autonomous systems can then also communicate with other cars and warn them in advance. This is called “Vehicle to Vehicle communication”. But communication is also done with infrastructure (which is called Vehicle to
According to various sources, we are in the middle of the so-called 4th industrial revolution. This revolution is basically lead by a very high degree of automation and IT systems. Until recently, IT played mainly a support role in the industry, but with new technologies the role will change dramatically: it will lead the industry. Industry 4.0 (or Industrie 4.0) is mainly lead by Germany which places a high bet on that topic. The industrial output of germany is high and in order to maintain it’s global position, the german industry has to – and will – change dramatically. Let’s first look at the past industrial revolutions: The first industrial revolution took place in the 18th century. This happend when the mechanical loom was introduced. The second industrial revolution took place in the early 20th century, when assembly lines were introduced In the 70th and 80th of the last century, the 3rd industrial revolution took place. Machines could now work
By Dietmar Gombotz, CEO and Founder of Sphares With the introduction and growth of different Cloud- and Software-As-A-Service offerings, a rapid transition process driven through the mix-up between professional and personal space has taken shape. Not only are users all over the world using modern, flexibel and new products like DropBox or others at home, they want the same usability and “ease of use” in the corporate world. This of course conflicts with internal-policy and external-compliance issues, especially when data is shared through any tool. I will focus mainly on the aspect of sharing data (usually in the form of files, but it could be other data-objects like calender-information or CRM data) Many organizations have not yet formulated a consistent and universal strategy on how to handle this aspect in of their daily work. We assume an organizational structure where data sharing with clients/partners/suppliers is a regular process, which will surely be the case in more than 80% of all