Frictionless Data Movement Across Apps In The Modern Enterprise

With the stock markets trading at record highs worldwide, there is a crop of day traders who make big bets and are in and out of the market. Picture such a trader needing to borrow a significant sum of money to execute a large trade. While a lending institution would certainly look at the credit profile and all the historical data, they would be well-served to see what the trader might have done that day – or what the previous transactions were. The up to the second risk profile handily beats the stale data.

The technology behind a truly real-time system such as this necessarily requires streaming of data – large volumes – and, in real-time, being stored in a database at the right location where machine learning models can be applied to provide the risk scores.

Use cases abound. Every interaction with the remote control is captured on how one watches programs – rewinds, pause, replay, ad-skips – and what that means for preferred content, serving specific ads, and providing customer service. The endless stream of real-time data from phones, smartwatches, and all other sources gets monitored by algorithms – which can then decide to notify the doctor or the emergency services based on the assessment of data.

This is no longer science fiction. Fast forward to 2025, and the amount of data your enterprise is dealing with is ten times what it was in 2021. Your customers are requesting more data than ever before, and you are offering the best-in-class customer experience based on data-driven insights. Data inside your enterprise flows freely in and out of internal systems on your private and public cloud infrastructure. Your business processes use data in real-time – when it’s most valuable and automatically identify and take the next best action on these real-time insights.

Your enterprise has moved from being reactive to proactive and from creating BI insights to implementing AI insights. Your data platform is a living system that never stops, the beating heart of your entire digital operating model.

There is no friction to data movement; data is available wherever needed, and your business can accommodate any initiative. All of this has been possible because you chose a data platform that provided the foundation for the digital transformation outcomes that are quickly becoming the standard in digital native companies worldwide.

Apache Pulsar and Apache Cassandra provide just such a foundation.

Apache Cassandra is an open-source, distributed NoSQL database that began internally at Facebook and provides the foundational storage for Apple, Netflix, and Spotify, among thousands of others. Cassandra delivers continuous availability (zero downtime), high performance, and linear scalability that modern applications require while also offering operational simplicity and effortless replication across data centers and geographies.

Apache Pulsar is a cloud-native, distributed messaging and streaming platform created at Yahoo! Pulsar builds on the capabilities of streaming products like apache Kafka adding essential features such as geo-replication, scaling, multitenancy, and queuing.

Together, Cassandra and Pulsar create an open, multi-cloud data platform, providing the architectural backbone for modern data applications for microservices, event-driven application stacks, real-time data, IoT/ML data, and more.

DataStax supports enterprises modernizing to an open, multi-cloud stack for modern cloud-native applications. DataStax delivers the freedom of choice, simplicity, and real cloud economics to deploy massive data, provided via APIs, powering rich interactions on multi-cloud, open-source, and Kubernetes.

Persistent brings superior consulting and implementation abilities to complement the products and DataStax offerings to make the vision of no-friction data movement a reality.

References

• Luna Streaming
• Four Reasons Why Apache Pulsar is Essential to the Modern Data Stack

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