Attuning Enterprises to the Growing Needs of Modern Applications

To reconcile enterprises with the growing demands of modern applications, new technologies and strategies are necessary to successfully support applications in their respective hybrid and multi-cloud environments.

DBTA hosted a webinar, “Powering Modern Applications: Data Management for Speed and Scale,” featuring speakers Rick Jacobs, technical product marketing manager at Couchbase; Mike Frasca, field chief technology officer at Reltio; Anais Dotis-Georgiou, developer advocate at InfluxData; and Mike Wong, solutions engineer at Unravel Data, to explore key solutions and best practices toward building modern applications in the wake of demands for real-time, cost effective, and streamlined processes.

Jacobs opened the roundtable talk by discussing the current climate of modern application requirements, emphasizing its widening gap between what used to be adequate for traditional applications. Modern apps necessitate modern databases, available 24/7, from anywhere and at any time. Massive amounts of data and users compounded with desires for scale and performance to match real-time demands, flexibility, microservices architectures, and optimized web, mobile, and IoT experiences dictate the reality of modern applications—and its database.

Couchbase is a NoSQL document database that highlights its ability to store data as complete objects; the primary record, as well as any additional records, are within a single document. Jacobs pointed toward its differentiators from competitors on the market as Couchbase’s advantage; it’s fast, flexible, familiar, and affordable, according to Jacobs. Its memory-first design, JSON document format, SQL++ query language, various SDKs, and high density storage are among the features that pose Couchbase as the solution for modern application modernization pain points.

Data is highly siloed and fragmented—an unfortunately, well-known adage within the data and technology industry. The complexities in managing data arise due to both data’s disparity and legacy MDM (master data management) standards; legacy MDM is cost prohibitive, limited, cumbersome, and a lengthy process, Frasca cited.

Reltio’s modern approach to MDM is built from the ground up within the cloud, targeting legacy MDM’s exact limitations. Through leveraging the cloud, Reltio can provide real-time performance, infinite scalability, and continuous accessibility to data. The modern MDM delivers upgrades and patches automatically, accompanied by a flexible data model that supports any data or storage type. Low code/no code capabilities make integration fast, and its native cloud structure means there’s no installation process. According to a report done by Forrester, the three-year impact for B2B and B2C operations employing Reltio indicated a 366% ROI gain with a NPV of $13 million.

Dotis-Georgiou discussed InfluxDB, InfluxData’s time series database platform, and its intrinsic value towards IoT application development and support. IoT applications require numerous things from a database: to be able to process data server side to increase performance, manage the time series lifecycle, alert users on data and monitor the application, and employ unified APIs to control instances.

InfluxDB, and its latest update InfluxDB Cloud 2.2, provides the advanced management and scaling of time series data. Equipped with a visualization layer for creating dashboards relating to the time series data, InfluxDB is as insightful as it is comprehensive. Its query and task engine further allows users to completely manage and pre-process time series data.

Data pipelines are creating strategic business advantages and companies are depending on them more than ever, according to Wong. Ultimately, complexity is what is slowing companies down; pipelines and stacks are made up of 6-20 systems, making them extremely difficult to manage. Compounded with the huge shortage of data engineers and operators, there exists a  backlog in data projects that directly impact enterprise success. Wong remarked that traditional DevOps tools cannot accommodate the contradictory needs of data applications and operations teams, citing the three “Big C’s” bogging down enterprises: costs, constraints, and complexity.

Unravel’s observability designed for the modern data stack aims to relieve organizations of the pressures of the modern data climate. Wong cited Unravel’s ability to monitor cost governance, quality, and performance as its ability to combat costs, constraints, and complexity. AI-enabled optimization and advanced troubleshooting minimizes meantime of resolution by aggregating disparate data around the data stack to one spot within Unravel, and then quickly performs a root-cause analysis to optimize infrastructure. Making sure data is accurate and precise, Unravel addresses the shortcomings of traditional DevOps tools in the wake of data complexity.