2014 was predictably dominated by open source platforms such as Apache Hadoop, KVM, NoSQL, Open Daylight and OpenStack. What are the open source platforms that could dominate 2015? Check them out below
1. ASP.NET vNext
Microsoft is synonymous with proprietary products garnering market share and brickbats in equal measure. They now are trying the Open Source route for web development since the world has moved to Cloud-based services where there is less scope for major revenue from proprietary products and services.
Developers around the world are quite excited about Microsoft’s roadmap for open-sourcing ASP.NET vNext, the next generation ASP.NET platform which:
- Is Open source
- Is Cross platform, can run on Windows, Linux, Mac
- Is Cloud optimized
- Is Server optimized to run on low memory and high throughput
- Application deployment with application, runtime, and framework packaged together to support side-by-side applications running on different .NET versions
- Is “no-compile compile” which means you can change your C# classes and hit refresh in the browser without the need to rebuild and restart the web server
vNext will be released along with Microsoft Visual Studio 2015; however, we can use any editor to write the programs and use free command line tools for compiling and building the application. The open-source community is expected to leverage the open-sourcing of ASP.NET vNext and come up with various IDE tools and enhancements of the product. This, in turn, will allow Microsoft to improve its market share into services offering open-source solutions and increase its footprint, thereby opening up more markets to sell its other related products.
For details, check out:
Introducing ASP.NET vNext on Hanselman Blog
Exciting Things About ASP.NET vNext Series
2. Docker
With Cloud-based applications becoming more sought after, there is demand for innovative cloud-based technologies that are more efficient and economical. Cloud-based applications are deployed in Virtual Servers or Hypervisor, which is a computer software, hardware, or firmware that creates and runs Virtual machines. Applications are deployed in different Virtual Machines, each with its own OS and framework, thereby sharing system resources and saving on hardware and space investment.
The newer Container Virtualization technology is still more efficient and economical in the sense that applications can be deployed on virtual containers which need not have their own OS, thereby freeing up the storage and memory space required for the OS. The containers run on a single OS of the host machine and share the resources more efficiently.
Docker is the most popular container technology used by many open-source vendors as well as promoted by proprietary vendors like Microsoft. It allows developers to build, deploy, and run distributed applications packaged for development, QA, and production environments seamlessly.
For details, check out:
What is Docker
3. OpenStack vs CloudStack
Cloud-based services are the future, and software products that dominate the cloud hosting market are quite few; they developed their technology faster than their competitors, thereby capturing the markets in its nascent stage itself.
OpenStack has been the leader in the pack for some time, while CloudStack has steadily improved on its chances to become the underdog. This year could be the beginning for CloudStack to match up to OpenStack’s top position in the market share and create its own dominant space alongside OpenStack.
The major difference between the two is limited to architectural setup. As more and more services are demanded by vendors from cloud platforms, the complexities of cloud management increase, and the architecture that proves itself flexible enough to handle these complexities will be most sought after. On these aspects, CloudStack hopes to depend on its more comprehensive architecture to pull it through.
For details, check out:
OpenStack vs CloudStack on Data Center Knowledge
4. Hadoop
BigData is something that is invaluable in the data space. With the amount of data growing to unimaginable levels, traditional systems found themselves short of capability to handle the avalanche of data. This inspired technology specialists to focus on dedicated software that can store, process, and analyze huge sets of data, termed as BigData.
Apache Hadoop has long dominated the BigData market, and there is no clear competitor for it at least in the near future. It enables parallel processing of a huge amount of data in a distributed environment on standard servers and can be scaled up seamlessly without limitations. Hadoop itself has become the standard among BigData players, offering its users exhaustive meaning to their data.
Many third-party vendors have introduced add-ins to leverage the power of Hadoop, offering the widest choices of additional features that can greatly leverage their data processing and analytics, including data storage, management, distributed clusters, and synchronization.
For details, check out:
Big Data Hadoop on SAS
5. NoSQL
NoSQL is not a new technology any longer, but it still maintains the excitement it created a few years back. Companies are cautious about moving away from traditional relational database management systems as they have the advantage of being tried and tested in the area of data storage and security. Newer companies and new projects are trying out NoSQL in a big way as more and more users vouch for the trust factor in the performance of open-source NoSQL databases. NoSQL is slowly chipping away the market share of Database leader Oracle so much that Oracle has come up with its own NoSQL and BigData products.
MongoDB is the leader in the NoSQL market with other players signaling their intent on investing more time and money to improve their NoSQL products. Beginning this year, NoSQL database vendors are poised to come out with more evolved products that can handle the data on a big scale like what major RDBMS vendors can handle.
Some users don’t look at NoSQL as an alternative to RDBMS, but have more effectively used a hybrid approach to use RDBMS and NoSQL to handle their data storage and analytics aspects. At the moment, this hybrid approach seems to be the best way to gain maximum throughput from data.
For details, check out:
NoSQL Databases Eat Into the Relational Database Market on TechRepublic
RDBMS vs NoSQL: How Do You Pick on ZDNet