Enterprises and organizations everywhere are being challenged by the demands for more interactions across channels, instant personalization, and more real-time data to drive better intelligence.
On the other hand, data is locked in legacy infrastructure and technology silos.
A data-first approach to modernization changes everything, from managing data as an asset, to modernizing and creating new applications.
You have different apps using NoSQL databases. Maybe it is a nationwide mobile curbside pickup app; or an app that authenticates tens of thousands of customers per second; or one that collects streams of sensor data to feed predictive analytics.
DataStax has created a multi-model database accessible via a developer-friendly API layer, enabling you to consolidate NoSQL workloads. This results in less operational complexity, more deployment options, and overall lower TCO.
Certain workloads need the velocity and the always-on availability that only a NoSQL database like Cassandra can deliver. You don’t even need to migrate everything off your legacy relational databases; only offload some workloads to begin with.
Where do you start? A smart migration journey begins by understanding the normalized tables, relationships, and queries trapped in your relational databases. Understanding these assets becomes a starting point for planning out the microservices to build. Only then can the team plan out the actual migration execution that does not disrupt the business.
Whether you’re building new apps or modernizing existing applications into microservices, success will come only if your data platform is up to date. Many microservices still rely on relational databases as a point of integration and to enforce consistency, resulting in compromised application performance and no agility. Start with data to guarantee performance and agility.
Performance, high availability, and linear scalability are all critical requirements when building microservice-oriented applications. But it must also be free of operational headaches and developer-friendly.
Fast modern applications result in delighted customers.
Business Agility
Small teams release innovative features fast and frequently
Lower TCO
No more exorbitant RDBMS license fees and less operational complexity
“The co-location of data and technology with Cassandra and Solr for search and Cassandra with Spark for analytics serves as the main benefit of DSE for Macquarie Bank. The results in the real-time nodes having access to data instantly and not requiring time-consuming or costly ETL processes to move data between systems because all data replicates in the cluster.”
Rajay Rai Digital Architect at Macquarie Bank
“One of the things I don't worry about at night anymore is a 10x growth in the catalog. We can easily handle that. It's just not a problem technically or for the business. If they want to grow the catalog, we can do it. And we can do it fairly inexpensively. I don't think that's necessarily the case with proprietary relational technologies.”
Peter Connolly Senior Architect, Macy's
“We wanted to implement a distributed database that would fit with our microservices-based application strategy and that would be able to handle the availability and scalability needs of the applications too. Cassandra matched this model perfectly, and the production support for DataStax Enterprise made a big difference. We considered other approaches based on SQL Server, but the distributed and always-on nature of DataStax Enterprise was a far better fit. The support from DataStax would also be essential as we moved into production—the company was the only option that would meet our needs around service-level commitments.”
Rune Birkemose Jakobsen Senior Development Manager at MobilePay
“We evaluated other NoSQL products, but the fact that large-scale organizations were using DataStax Enterprise successfully gave us the confidence that DataStax could handle our performance and scalability requirements.”
Mark Dash Assistant VP of Information Technology at Penn Mutual
“The DataStax Enterprise environment is a horizontally scalable data environment; once the demands on that environment increase, we add more nodes to the cluster to expand the capabilities without any downtime.”
Ken Chenis Chief Architect at ACI Worldwide
“Our service for customers is based on providing real-time analytics and alerts based on global and multilingual data. That could be alerting customers to a disaster near to one of their sites, demonstrating potential security risks, or for competitor analysis. What powers this is our ability to make connections in our data, and for that we rely on DSE Graph.”
Dirk Kolb CEO at Traversals
More Resources
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Kubernetes is everywhere. Transactional apps, video streaming services and machine learning workloads are finding a home on this ever-growing platform. But what about databases?
