By Jonathan Ellis, Cofounder and CTO, DataStax
Messaging has been on DataStax’s radar for several years. A significant motivator for this is the increasing popularity of microservices-based architectures. Briefly, microservices architectures use a message bus to decouple communication between services and to simplify replay, error handling, and load spikes.
With Apache Cassandra™ and DataStax Astra Cassandra-as-a-service, developers and architects have a database ecosystem that is:
There is no current messaging solution that satisfies these requirements, so we’re building one. We started by evaluating the…
By Chris Bartholomew, Streaming Engineering, DataStax
Author’s note: I originally published this blog post in 2019, while I was CEO of Kesque, a real-time messaging service built on Apache Pulsar, the cloud-native distributed messaging and streaming platform. It’s a follow-up to an earlier post, “7 Reasons to Choose Apache Pulsar over Apache Kafka.” A lot of big changes have happened since these two posts went live, including Kesque’s acquisition, in January, by DataStax. The reasons to choose Pulsar, however, haven’t changed.
A while back, I wrote a post about the 7 Reasons We Choose Apache Pulsar over Apache Kafka. Since…
By Sam Ramji, Chief Strategy Officer, DataStax
Along with tens of thousands of developers and operators, and companies ranging from startups to titans like Apple and Netflix, we want to see Apache Cassandra™ become cloud-native.
We have done the work required to have an opinion: Astra is built on Kubernetes, Prometheus, Envoy, and participates in the GKE and EKS native control and management planes. We’ve reviewed work done by others, particularly those who have shared what they have learned in the form of open-source Kubernetes operators for Cassandra.
The opinion expressed in Astra is based on the technical work, changes…
Check out our new eBook on working with Kubernetes and Cassandra
The cloud has transformed enterprise technology in ways that nobody could have imagined a decade ago. Enterprise development teams are trying to adapt at lightning speed to building, deploying, and running cloud-native applications. They’ve had to learn new ways to work with distributed application architectures and containerized environments and are mastering the challenges of designing applications that run flawlessly at a massive scale.
Success with cloud-native applications requires enterprises to make weighty platform choices that will shape everything they do — for better or worse — for years to…
By Ed Anuff, Chief Product Officer, DataStax
In working with dozens of leading enterprises to help them implement a wide range of multi-model use cases, I’ve noticed a significant shift in why and how organizations use multi-model databases.
What historically drove enterprise adoption of multi-model databases was the flexibility they provided in data modeling. A multi-model database stores multiple data types in their native form, using a single back end, with unified data governance, management, and access.
But that flexibility isn’t flexible enough anymore. As the pace of change in customer demands and business requirements has accelerated, so have the…
By Chris Bartholomew, Streaming Engineering, DataStax
Author’s note: I wrote an earlier version of this blog post in 2019, while I was CEO of Kesque, a real-time messaging service built on Apache Pulsar, the cloud-native distributed messaging and streaming platform. A lot of big changes have happened in the interim; perhaps the most significant of these is the fact that the company I founded in early 2019 was acquired, in January, by DataStax. One thing that hasn’t changed, however, is the rationale behind our choice of Apache Pulsar.
At Kesque, it was our mission to empower developers to build cloud-native…
By Denise Gosnell, Chief Data Officer, DataStax
The market for graph databases is expected to nearly triple by 2024, and for good reason: graph technology enables organizations to build applications that meet ever more demanding user expectations. So, what exactly are users demanding that graph solves? Users are demanding personalized context.
Although graph data is becoming more and more integral to the success of the data-driven enterprise, the technology is still in a relatively nascent stage for enterprises. We are, however, seeing graph technology pick up a lot of traction. …
By Patrick McFadin, VP of developer relations, DataStax
As serverless methodologies have burned through the application tiers, databases have been the last big thing to feel the heat of progress. But that’s changing.
The dreaded part of every site reliability engineer’s (SRE) job eventually: capacity planning. You know, the dance between all the stakeholders when deploying your applications. Did engineering really simulate the right load and do we understand how the application scales? Did product managers accurately estimate the amount of usage? Did we make architectural decisions that will keep us from meeting our SLA goals? And then the question…
T-Mobile EVP, CIO and Chief Product Officer, Cody Sanford talks about T-Mobile’s customer-obsessed approach with DataStax Chairman and CEO Chet Kapoor.
The fourth episode of the Inspired Execution podcast is hot off the proverbial presses. In it, T-Mobile EVP, CIO and Chief Product Officer, Cody Sanford shares insights about:
Welcome to our new Q&A series: Behind the Innovator
Behind the Innovator takes a peek behind the scenes with learnings and best practices from leading architects, operators, and developers building cloud-native, data-driven applications with Cassandra and open source technologies in unprecedented times.
For our inaugural interview, we talked to Mike Heinen, the customer platform operations manager at Cengage, a leading education and technology company built for learners.
Here’s what he had to say.
1. Tell us about your background and what you do in your position.
I’ve been with Cengage for about 15 years. Cengage is the largest U.S.-based education…
DataStax is the company behind the massively scalable, highly available, cloud-native NoSQL data platform built on Apache Cassandra™.