Database and appliances

Trend 1. Accelerated migration from proprietary databases and appliances to open-source and cloud platforms

With digital transformation of businesses comes huge capital and time investment in new, innovative technologies. Cloud computing is a major trend in digital transformation, as it makes business applications and infrastructure easily accessible. According to Gartner, 75% of databases will be deployed or migrated to a cloud platform by 2022. This is driven largely by the use of databases for analytics and the software-as-a-service model.

In the journey toward Cloud Migration , businesses are looking to reduce costs. It’s one of the primary reasons businesses want to move from proprietary to open-source databases. According to EnterpriseDB, with a shift to PostgreSQL, up to 65% of costs can be saved.

As cloud computing gains adoption, DBaaS (database as a service) has also risen. With DBaaS, enterprises don’t have to deal with complex infrastructure, and databases are managed and supported by their respective vendors. MySQL and PostgreSQL are provided by major cloud vendors. With infrastructure being managed by cloud vendors and open-source databases being easily available, more organizations are shifting toward DBaaS.

Infosys collaborated with one of the largest multinational investment banks to help migrate from appliances like Teradata to Hadoop data platform.

Infosys partnered with a large financial service company, to create an experience layer based on AeroSpike to decouple customer facing systems from mainframe DB2 SOR, for their trading platform.

Database and appliances

Trend 2. Increasing adoption of varieties of NoSQL databases

NoSQL, or nonrelational database, adoption is rising as enterprises develop a need to access and analyze large amounts of unstructured data or the data stored in multiple virtual servers in the cloud. RDBMS encountered few limitations while handling unstructured data, which led to the pioneering of NoSQL databases by top internet companies including Amazon, Google, LinkedIn and Facebook.

These include varieties of NoSQL databases such as key value store (Redis, Riak and Couchbase), columnar (Apache’s Cassandra and HBase), document (MongoDB and Couchbase), and graph databases (Neo4j and JanusGraph).

Database and appliances

Trend 3. Convergence of transactional and analytical data

Enterprises generally have transactional, analytical and operational workloads across separate data warehouses, data lakes and databases. This leads to data silos, making it difficult to provide real-time analytics and insights without movement of data across these systems.

This process of moving data is slow and cumbersome, and it reduces competitiveness of enterprises in today’s digital world. Businesses find challenges in giving price quotes to their sales team in real time, monitoring assets or making product recommendations. Likewise, supply chain partners may not have updated inventory or shipping details.

This leads to the emergence of architecture where online analytical processing and online transactional processing are merged into a single platform. It helps in performing advanced analytics and providing insights and recommendations in real time, while also conveniently displaying live transactional data on one platform.

These databases drive real-time apps, like for fraud detection, patient health monitoring, counterterrorism, stock trading and earthquake monitoring. They also have applications in asset monitoring and provide connected data apps, giving a view of critical business data.

Infosys partnered with one of the largest sportswear manufacturers to build a near real-time event streaming-based solution to ingest and analyze a huge number of events generated through a mobile app, internet for user activity analysis.

Infosys collaborated with one of the largest multinational chains of coffeehouses for accelerated onboarding of new data products through a Multi-point Metadata driven Ingestion Framework. Auto Generation of Data Flow pipelines was done with Extreme Automation.

Infosys partnered with a government agency to build end-to-end tax collection and tax accounting systems on an opensource platform using an agile development process to meet the unique characteristics of the system.

Infosys partnered with one of the largest oil and gas corporations to create an Integrated Data Marketplace to provide users with a platform to find data, tools and practices to conduct research, develop web and mobile applications, design data visualizations. Also, provide platform/tools for self-service analytics.

Infosys collaborated with one of the largest telecom companies for enhanced user experience through Flexible Dashboards, Analytics Reporting by integrating Insight360 with Data Café’s features like Report mashup, KPI mashup, storyboard, additional administrative functionalities, coupled with Robust Security and Data Governance.

Infosys partnered with one of the largest pharmaceutics companies to create an end-to-end analytics platform on cloud that provides a template-driven approach for data onboarding, device-independent architecture to scale for future and advanced AI/ML support to enable analytics at scale.


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