Managing Exponential Data Growth and Enabling Application Scalability through Data Modernization

The exponentially growing volumes of data and need for applications to scale in order to support organizational growth are key factors in the data modernization trend. Although old-school applications, built on monolithic architecture are effective, they are limited in terms of scalability.

80% to 90% of the data that a modern organization has to store and process is unstructured data in various formats. Traditional RDBMS are not up to the task of storing this unstructured data. Moreover, the volume of this unstructured data is growing at an exponential rate, much faster than a traditional database can handle. It is challenging to analyze this massive amount of unstructured data for actionable insights.

In addition, there is increasing need for compliance with industry regulations for data privacy, security and management. Traditional databases do not have functionality that inherently supports these requirements and given their structure, data is not spread across locations to support disaster recovery.

Modernizing data and applications through cloud-friendly, no SQL databases caters to all these requirements – they can easily store unstructured data, they can scale with ease and data in the cloud is not tied to a single location. Making the transition to a modernized database enables greater scalability and automation, which enhances operations and gives businesses a competitive edge.

Impact on Application Development

Modern, no SQL databases and cloud native applications in containers are the technological response to the first two challenges. This technological shift enables organizations to add more resources and scale and update applications much faster than traditional, monolithic databases and application environments would allow. Cloud native applications run in containers that are organized into clusters of individual, discrete microservices instead of a rigid, slow, single, monolithic application environment.

Research indicates that by 2022, 75% of databases and 90% of new applications will be in the cloud. Leveraging containers for cloud applications enables flexibility, scalability and the ability to adapt to new opportunities faster.

Cloud computing can distribute applications on several compute nodes at different locations. It enables component reuse, extremely fast deployment and patching, isolation of processes to improve security and quick and selective burst of application components. All this functionality empowers organizations to scale up or down quickly and easily as required.

Importance of Persistent Storage

There have been some limitations with regard to compliance and analysis of data in cloud native applications that use containers. Any data that is in a containerized application process is gone once the container shuts down, unless the application uses persistent storage for that data. This is increasingly necessary, as companies need to store data for various legal, security or audit policy compliance. Another challenge is that companies often need to access and share this persistent data with clients or business partners in other organizations. Sometimes this data needs to be shared across separate applications or app instances.

Given the massive explosion in the volume of data generated, and the fact that it is in formats such as videos, image, texts and documents, it is a huge challenge to manage unstructured data at scale while staying cost-effective. This is where modern databases bridge the functionality gap allowing long-term storage, analysis and management of data through persistent storage.

Modern Databases for Persistent Storage

Modern, cloud- enabled databased provide rich functionality that support persistent storage of all formats of structure, semi-structured and unstructured data in a highly cost-effective, easily accessible manner. They support a range of data management requirements enabling organizations to share data between functions and services, or with end users as well as complying with regulations. They also support persistent data volumes, storage service classes, Kubernetes, containers and API integration.

Such modernized databases also provide enhanced functionality for data governance and policy management. You can ensure that your persistent data is in compliance with all relevant industry, government and ISO standards regarding data privacy. Set retention and expiration time frames for data and control data access. Maintain the security of persistent data through encryption while data is in transit or at rest.

Once persistent data is in the cloud, it is available anytime, anywhere as long as you have a device with an internet connection. This cloud availability and distribution of data across several data centers and locations provides stronger availability and resiliency of data. Using a modernized database supports a range of environments including containers as well as Kubernetes so you can store persistent data from containerized apps with all the advantages of cloud storage.

Why DataSwitch?

DataSwitch is a trusted partner for cost-effective, accelerated solutions for digital data transformation, migration and modernization through a Modern Database Platform. Our no code and low code solutions along with enhanced automation, cloud data expertise and unique, automated schema generation accelerates time to market.

DataSwitch’s DS Migrate provides Intuitive, Predictive and Self-Serviceable Schema redesign from traditional model to Modern Model with built-in best practices, as well as fully automated data migration & transformation based on redesigned schema and no-touch code conversion from legacy data scripts to a modern equivalent. DataSwitch’s DS Integrate provides self-serviceable, business-user-friendly, metadata based services, providing AI/ML driven data aggregation and integration of Poly Structure data including unstructured data. It consolidates and integrates data for domain specific data applications (PIM, Supply Chain Data Aggregation, etc.). DataSwitch’ s DS Democratize also provides intuitive, no code, self-serviceable, conversational AI Driven “Data as a Service” and is intended for various data and analytics consumption by leveraging next gen technologies like Micro Services, Containers and Kubernetes.

Choosing an automated data and application modernization platform minimizes the risks and challenges in your digital transformation. It is faster, highly cost-effective, eliminates error-prone manual effort and completes the project in half the typical time frame. Book a demo to know more.