2025 Future Hybrid FastData + SmartData

Big data it’s exponentially increasing daily in a hyper-rate and will be the next power for companies to exploit into the cloud.The majority of big data experts agree that the amount of generated data will be growing exponentially in the future. In its Data Age 2025 report for Seagate, IDC forecasts the global datasphere will reach 175 zettabytes by 2025. What makes experts believe in such a rapid growth? First, the increasing number of internet users doing everything online, from remote working, home school, business communications to shopping and social networking will be increased by 50% in 2025.

As enterprises gain the opportunity to store and analyze huge volumes of data, they will get to create and manage 60% of big data in the near future. However, individual consumers have a significant role to play in data growth, too. In the same report, IDC also estimates that 6 billion users, or 75% of the world’s population, will be interacting with online data every day by 2025. In other terms, each connected user will be having at least one data interaction every 18 seconds.

Such large datasets are challenging to work with in terms of their storage and processing. Until recently, big data processing challenges were solved by open-source ecosystems, such as Hadoop and NoSQL. However, open-source technologies require manual configuration and troubleshooting, which can be rather complicated for most companies. In search for more elasticity, businesses started to migrate big data to the cloud.

AWS, Google Cloud Platform and IBM have transformed the way big data is stored and processed. Before, when companies intended to run data-intensive apps, they needed to physically grow their own data centers. Now, with its pay-as-you-go services, the cloud infrastructure provides agility, scalability, and ease of use.

This trend will certainly continue into the 2020s, but with some adjustments:

• Hybrid environments. Many companies can’t store sensitive information in the cloud, so they choose to keep a certain amount of data on premises and move the rest to the cloud.
• Multi-cloud environments. Some companies wanting to address their business needs to the fullest choose to store data using a combination of clouds, both public and private.

Machine learning will continue to change the landscape and playing a huge role in big data, machine learning is another technology expected to impact our future drastically.

Not until recently, machine learning and AI applications have been unavailable to most companies due to the domination of open-source platforms. Though open-source platforms were developed to make technologies closer to people, most businesses lack skills to configure required solutions on their own. Oh, the irony.

The situation has changed once commercial AI vendors started to build connectors to open-source AI and ML platforms and provide affordable solutions that do not require complex configurations. What’s more, commercial vendors offer the features open-source platforms currently lack, such as ML model management and reuse.

Meanwhile, experts believe that computers’ ability to learn from data will improve considerably due to more advanced unsupervised algorithms, deeper personalization, and cognitive services. As a result, there will be machines that are more intelligent and capable to read emotions, drive cars, explore the space, and treat patients.

Yet another prediction about the big data future is related to the rise of what is called ‘fast data’ and ‘actionable data’.

Unlike big data, typically relying on Hadoop and NoSQL databases to analyze information in the batch mode, fast data allows for processing in real-time streams. Because of this stream processing, data can be analyzed promptly, within as little as just one millisecond. This brings more value to organizations that can make business decisions and take actions immediately when data arrives.

Fast data has also spoilt users, making them addicted to real-time interactions. As businesses are getting more digitized, which drives better customer experience, consumers expect to access data on the go. What’s more, they want it personalized. In the research cited above, IDC predicts that nearly 30% of the global data will be real-time by 2025.

Actionable data is the missing link between big data and business value. As it was mentioned earlier, big data in itself is worthless without analysis since it is too complex, multi-structured, and voluminous. By processing data with the help of analytical platforms, organizations can make information accurate, standardized, and actionable. These insights help companies make more informed business decisions, improve their operations, and design more big data use cases.

The database management system(DBMS) is a software which helps the user interact with the database. Simply put, a database is the collection of data in form of tables, queries, reports and similar objects. Most of the databases that are in the market today are relational databases. Oracle’s MySQL, IBM’s DB2, Microsoft’s Access are all relational databases. A relational database is a digital database in which data is organized in tables with each row of the table having a specific key. It is far better than the earlier hierarchal databases of the past which where slow and less organized.

But, times are changing fast. Today you can be satisfied in using a relational databases which are exclusively based on the structured query language (SQL). But the future is already upon us with NoSQL and NewSQL gaining ground. With the need to store, study and manage large amounts of data these flexible and powerful standards are ready to win over traditional database languages.

NewSQL, in-turn is a hybrid database management system which adds the capabilities of NoSQL to the ACID capabilities of a relational database. These systems find vast applications in the OLTP (Online Transaction Processing) section.

This truly has developed an interesting situation with established database providers feeling the heat. In addition, the data owners have an even field to choose among several distinct options. This situation led to the rise of several solutions with broader differences among each of them. These include Cassandra, HBase (column databases) Mongodb, CouchDB (document databases) Redis (key-value), VoltDB, Hypertable, Accumulo etc.

With on-premise database infrastructure and legacy systems slowly fading, agile, scalable, cost effective database management in the cloud is taking over.

This is because organizations now understand that to adopt to the innovations in database management system (DBMS) they need to move to the cloud. DBMS on cloud offers flexible pricing models, no capital expenses and better operating expense leveraging the pay-as-you-go model. Unsurprisingly then, the popularity of ‘database as a service’ is increasing.

What is cloud database as a service?

Cloud database as a service (DBaaS) enables an organization to access, alter and manage corporate data without the need to setting up on-premise infrastructure. The DBMS is hosted on a cloud which frees the operations and maintenance personnel from the routine tasks necessary for running the enterprise database. When a database cluster is in the cloud, everything concerned with the infrastructure is dealt with and managed by the cloud provider. This allows the enterprise to concentrate better on its actual business objectives. Cloud DBaaS is gaining in popularity because big businesses are able to cut back costs on infrastructure and manpower and spend on value additions to their core products and services.

Shift towards cloud-native architecture

It is a well-known fact that more and more organizations are adopting cloud infrastructure. They are not only moving their generic business process applications on to the cloud, but also their mission critical applications and data.

According to recent industry research, 80% of all databases will be deployed or migrated to a cloud platform by 2025. This means that organizations are in need of cloud services and solutions that will support their cloud native architecture. In fact, business organization are developing or sourcing cloud native applications since it allows the business processes to be more dynamic. This goes for their database management system as well.