What is DataStax ?
DataStax provides the open data management stack serving real-time applications. It is the expert in the Apache Cassandra open source NoSQL database and the Apache Pulsar streaming solution.
This open source stack, connected to the rest of the data landscape, allows developers and companies to:
- Mobilize real-time data in a multi-cloud architecture, based on Kubernetes.
- Rapidly develop intelligent applications with a wide range of APIs and templates.
- Scale data without excessive complexity or cost thanks to a serverless architecture.
JEMS integrator DataStax
Companies rely on us to gain market share by improving the customer experience they deliver through a holistic view of interactions, trends, and relationships and by providing real-time personalized services and recommendations.
Our DataStax integration enables them to gain efficiencies by bridging devices, data, and people, and managing an explosion of information that changes very quickly – and is available at any time if they need it.
Finally, DataStax helps shorten their time to market through products, services and training as well as a strong partner ecosystem that makes it easier for them to develop and manage cloud applications while eliminating the complexity and risk involved.
The JEMS x DataStax offer
The world’s most widely used digital experiences, the most critical services, such as Apple iCloud and Netflix exist because of Apache Cassandra. The DataStax open stack and JEMS approach allows companies to build applications and products that will change their digital trajectory on the same technologies and best practices.
DataStax guarantees companies:
- The choice of deployment: public cloud, hybrid or on-premises.
- Choice of operating mode, either customer-operated or DataStax-operated
- Choice of APIs and model.
JEMS completes the stack with its skills to deliver an integrated approach from conception to production, including
- Establishing the data strategy to achieve digital goals.
- Defining and changing the data architecture and models.
- Real-time connectivity of the stack to the rest of the data landscape
- Using the data for machine learning or analytical applications
Customer Story: TEREOS – Optimizing beet collection and supply chain with data
Case Study : LVMH: Deploying a global 360 vision with Google
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