HomeBUSINESSOpen Source Solutions In Data Management

Open Source Solutions In Data Management

The management of ever-increasing amounts of data poses the question for companies: should they use proprietary, open-core or open-source solutions? Cost efficiency, scalability, flexibility, security and, above all, independence speak in favour of the open-source alternative.

With the explosion of data to manage, organizations need powerful data layer technologies. In doing so, they have to decide whether they want to use proprietary or open-source software.

To make matters worse, there are also open-core solutions that appear open source but are proprietary applications built on open source code. The technology selection of companies in this regard has far-reaching consequences for the long-term architecture orientation, data management, the required employee know-how and the budget.

Proprietary solutions promise stability and unified, fully integrated management. In addition, they often have performance features for which there are no alternatives at first glance. Proprietary software, however, is often inflexible and expensive and always leads to vendor lock-in.

Closely related to open source, the open-core model is based on open-source technologies that companies add proprietary functionality. They then create a commercial version of the software they control. This also creates a dependency for users.

In contrast to proprietary applications, open-source is in principle free and open. The advantages lie in costs, flexibility, scalability, transparency and security. In addition, the user has maximum freedom in the choice of technology.

Open Source As The Best Choice

When weighing the respective advantages and disadvantages, there is a lot to say about the pure open-source version. And there is already a growing trend for companies to replace proprietary technologies with open source. They not only want to reduce costs, maximize flexibility and reduce dependency but also benefit from the dynamic and innovative developments of the open-source communities.

Simple open-source solutions have become more attractive, especially for developers. Surveys show that Redis or PostgreSQL are among the most popular databases. On the other hand, proprietary databases such as IBM Db2 and Oracle are becoming less important.

So if a company is currently using a proprietary data layer solution, they should consider moving to trustworthy open-source. The first step is to check to what extent there are open source alternatives to the proprietary functions that are required. It quickly becomes apparent that such options are generally available. For example, proprietary solutions are often used to replicate topics between clusters.

The open-source alternative to this is Apache Kafka MirrorMaker 2, allowing enterprises to mirror clusters, with various cluster topologies supported. Several companies also use proprietary applications to index, search and analyze their data. There are numerous open-source alternatives for this, such as SASI indexes for Apache Cassandra, Apache Lucene Index for Apache Cassandra or OpenSearch.

These three examples show how open source technologies can easily replace proprietary functions. It is often not too difficult for niche applications with no open-source solution to develop the required procedures yourself or with external support. Such an approach is still very cost-effective in the medium and long term since no license fees are incurred.

Before migrating from a proprietary to an open-source solution, it is a good idea to create a detailed migration plan. Essential components are a feature gap analysis and a health check. The gap analysis determines whether there are still gaps in the software’s functionality used in the future that need to be closed using open source alternatives.

In the health check, the current IT infrastructure is checked and evaluated – for example, concerning configurations and processes, the data model or monitoring. On this basis, a company can then determine optimization options and specify the requirements for a new solution.

Various approaches are then conceivable for the actual migration: from continuously migrating individual nodes into a cluster to creating a new mirrored collection. A company has to decide on a concrete migration model individually – external support from experts can be beneficial.

Managed Platform Approach Offers Flexibility And Security

If a company is unsure whether the conversion to open source will be successful with the available resources and employees, it can fall back on external support. For example, experts can be brought in to train your team to safely handle the migration process and the management of the chosen technology.

It is also possible to commission external IT service providers or consultants to carry out the migration. In addition, a company can also use the services of a managed platform provider for open source technologies. This relieves your employees of activities related to database administration so that they can focus more on more productive and innovative tasks.

High scalability and flexibility also speak for managed platforms. In this way, companies can operate their IT infrastructure entirely in the cloud, in hybrid or multi-cloud environments. If you have security concerns, you can also use a managed platform. In principle, however, when it comes to security, it should be noted that with managed platforms, control of the data layer always remains with the company and not with the service provider.

If a company relies on a proprietary solution, it may be reluctant to leap to open source. Reasons can be the imponderables regarding the difficulty of the migration, the technological know-how of the own team or the loss of proprietary functions.

However, moving to open source isn’t rocket science with the proper planning and strategy. And the advantages for companies are compelling: they get more cost-effective, high-performance solutions that are part of a comprehensive ecosystem that is continuously evolving along with their application stack.

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