With super-accelerated global digitalization, application development demands are skyrocketing. Current and legacy database management systems need a shakeup …
According to EY analysts, Asian businesses need to proactively boost customer experiences and omnichannel commerce.
While it is vital to continually add new functionalities to applications to keep up with modern requirements, this often burdens developers and servers with increasingly complex data challenges. Developers should therefore strike a balance between structural consistency and agility.
One key hurdle that developers face is the organizational reliance on traditional legacy databases. Not only are SQL-databases unsuitable for many of the latest application requirements, many businesses today consider these as legacy technology: hindering progress and limiting the capabilities of modern applications.
The push to develop cloud-based applications is driving developers away from relational databases and towards serverless development strategies. Not only does the latter reduce the time-to-market for a product, but they also reduce post-deployment operational costs because developers do not need to worry about underlying infrastructure when writing and deploying code.
Microservices: great but with a caveat
To adapt to this new environment, developers are beginning to adopt cloud-native practices like continuous integration and delivery. Microservices are the perfect tool to allow continuous development with no impairment on continuity. When each feature of an application has its own microservice, adjustments can be made to separate components without modifying the application as a whole — meaning no downtime is required to make modifications.
However, with agility comes risk. Security is a significant concern for organizations looking to move towards cloud-computing. With this in mind, organizations must consider how new data and features can be added to applications safely, and whether developers have the tools and knowledge to achieve this.
From a development perspective microservices provide unparalleled agility, but the challenges of data sprawl and data stack could unlock the potential for new opportunities in the cloud segment.
As application development becomes more modular — and data requirements per application continue to grow — a single system could end up using thousands of databases. Eventually, servers cannot cope with data requirements, searches slow down, and user experience is impacted.
Data sprawl causes loss of productivity, impacts consumer experience and slows down employee performance when they are trying and waiting to retrieve data.
In applications with multiple databases, particularly as new features are added, compromises in functionality and security are common. As applications grow, data may become inconsistent, duplicated, and may no longer meet security requirements. This slows down development, causes issues with integration, and increases the complexity of administration — ultimately increasing costs.
Taking control
Database management is an overarching problem in modern business. Development teams need to be efficient and bring applications to market fast. Learning and rewriting code so that new search capabilities can be added is inefficient, impacts performance, and slows down innovation. This is where “multi-model” database systems with full automation come in.
With their capacity to conduct multiple functions or services with a single database, flexible deployment, and cross data center replication, multi-model databases could be a developer’s new best friend. As the name would suggest, multi-model databases support multiple data services in a single database platform.
Not only does this facilitate the building of microservices quickly, but consolidation of databases is also a benefit. This means sensitive data is better protected; automation simplifies administration; and both software and hardware costs are reduced through the elimination of redundancy.
By taking advantage of the improved analytics provided by multi-model databases, businesses can improve how they use and collect data on customer profiles and trends to gain actionable insights to boost customer experience and satisfaction.
Other applications of multi-model databases include the use of cross data-center replication and memory-first architecture to reduce response times and implement multi-dimensional scaling of data services with no loss in latency.
As we develop applications of the future, their core building blocks — and the data — must be managed effectively. Microservices continue to demonstrate their value, providing the agility, adaptability, and speed but mediating data sprawl will be a key challenge going forward. This is where multi-model databases can be the answer to tomorrow’s application development challenges.
