Modernization is on the minds of IT decision makers, and with good reason – legacy systems cannot keep up with the realities of today’s business environment. Additionally, many organizations are discovering their modernization advantage: their developer teams, and the databases that underpin their applications.
“Legacy Modernization is a truly strategic initiative that enables you to apply the latest innovations in development methods and technology to refresh your portfolio of applications,” says Frederic Favelin, EMEA Technical Director of Partner Presales at MongoDB.
His remarks came during an episode of Google Cloud’s podcast series “The Principles of a Cloud Data Strategy.”
“It’s so much more than just lift and shift,” Fevelin continues. “Moving your existing applications and databases to faster hardware or the cloud may give you slightly higher performance and a modest reduction in cost, but you can achieve transformational business agility and scale, or development freedom, without modernizing the entire infrastructure.” fail to realize.”
For many organizations, databases have proliferated, creating a complex ecosystem of resources – cloud, on-premises, NoSQL, non-relational, traditional. The problem, Fevelin says, is organizations deploying non-relational or no-SQL databases as “band aids to compensate for the shortcomings of legacy databases.”
“So they quickly find that most non-relational databases only excel at a few specific things — specific things — and they have really limited capabilities, like limited queries, capabilities, or lack of data consistency,” Fevelin says. Huh.
“So it is at this point that organizations are really trying to learn, maintain, and figure out how to integrate data among a growing set of technologies. This often means that data infrastructure has different- Separate search techniques are added, requiring teams to move and transform data from databases to dedicated search engines.”
Add the need to integrate increasingly strategic mobile capabilities, and the environment becomes even more complex. In addition, as organizations strive to provide a richer application experience through analytics, they sometimes need to use complex Extract, Transform and Load (ETL) operations to move operational data into a separate analytical database. is required to do.
It adds even more time, people, and money to day-to-day operations. “So at MongoDB, we give it a name: doing innovation,” Fevelin says.
Towards a Modern Ecosystem
Favelin says that a modern database solution must meet three important needs:
It should address the fastest way to innovate, with flexibility and a consistent developer experience. It must be highly secure, have database encryption, and be fully audible. Thereafter the freedom and flexibility to deploy on any infrastructure—starting with laptops, moving to the cloud, and integrating with Kubernetes. It should be scalable, flexible and mission critical with auto scaling. Finally, offering a unified modern application experience means that developer data platforms need to include full text search capabilities, be operational between transactional workloads and analytical workloads. Freshness of transactional data for analytical data to be as efficient as possible to provide the best experience for users.
“The MongoDB Developer Data Platform helps ensure a unified developer experience,” says Fevelin, “not only across various operational database workloads, but across data workloads, including search mobile data, real-time analytics, and more.”
Check out the “Principles of Cloud Data Strategy” podcast series from Google Cloud on Google Podcasts, Apple Podcasts, Spotify, or wherever you get your podcasts. Get started with MongoDB Atlas on Google Cloud on the Google Marketplace today.