Big Data 50: Companies Driving Innovation in 2021

DATASTAX HAS A MISSION to deliver products that developers love and change the trajectory of enterprises.

The world runs on Apache Cassandra and DataStax was created to make the world’s most scalable database easier to run and manage, deploy the future of modern cloud applications cost-effectively and free enterprises from cloud vendor lock-in. We do that by shattering the traditional methods of managing real-time data and solving pain points for developers, while delivering always-on business continuity and bringing the power of Cassandra to every developer and enterprise, for mission-critical workloads. With DataStax, any developer or enterprise can now deploy data at massive scale, with 100% uptime, for lower cost.

Through a unique open data stack for the future, DataStax empowers any enterprise to tap the power of data without limits, providing a solution that is:

• Kubernetes-based for cloud-native agility
• Developer-ready with APIs to reduce time to market for new apps
• Cloud-delivered to simplify operations and reduce TCO

Uniquely positioned to deliver the modern database of the future, DataStax harnesses its power to solve real business problems by making the distribution of data easy to scale, accelerating the data-driven enterprise and streamlining developer operations.

Today, nearly 500 of the world’s most demanding enterprises and half of the Fortune 100 rely on DataStax to power modern data apps, including Netflix, The Home Depot, T-Mobile, Intuit and so many more.

DataStax
www.datastax.com

Big Data Trailblazer by Ravi Shankar, Senior VP & Chief Marketing Officer

The term “big data” has been around for many years, in many respects it has come to mean almost everything and nothing at the same time. This is not the fault of the data, but more so how people use it and interpret it.

Why is this the case? there are many factors, but essentially if you can’t see the wood for the trees, it is hard to gain value from the data. Big data systems fail to become the single repository for all enterprise data. Organizations stumble on the challenges of moving/storing data of different types especially in multi cloud/hybrid cloud enterprises. It is quite common for no one person in an organization to have that single view of the data, organizations spend more time collecting data than they do analyzing it. ETL processes are often the tool of choice when organizations look to integrate siloed data. ETL processes are scripted to move data in batches and fail to deliver real time insights. They also fail to accommodate new sources without extensive testing and coding, and of course even more challenging are more modern data formats such as streaming IoT or unstructured data (which actually are often the real key to success in big data projects).

Data virtualization on the other hand is a data integration technology that integrates data in real time, without the need for replication. Data virtualization allows organizations to establish flexible modern disparate logical data architectures such as a logical data fabric, allowing them to draw data seamlessly across silos of a big data implementation.

The award-winning Denodo Platform offers the most advanced data virtualization capabilities available for establishing a logical data fabric to maximize big data investments. Its built-in data catalog provides seamless access to data via a searchable, contextualized interface, and in-memory parallel processing accelerates data access to unparalleled speeds.

Denodo Technologies
www.denodo.com

Big Data Trailblazer by Jans Aasman, CEO

ENTERPRISE KNOWLEDGE GRAPHS FOR A MODERN BIG DATA ARCHITECTURE

Industry analysts recognize the power of Knowledge Graphs in delivering a modern big data architecture that provides integrated, trusted, and real-time views of enterprise data. The accelerating adoption in the enterprise of this Knowledge Graph approach, which unifies business data with knowledge bases, industry terms, and domain knowledge, is clearly the future of AI and advanced analytics.

Franz’s AllegroGraph platform further extends this modern Knowledge Graph approach with a novel Entity-Event Model, natively integrated with domain ontologies and metadata, and dynamic ways of setting the analytics focus on all entities in the system (patient, person, devices, transactions, events, operations, etc.) as prime objects that can be the focus of an analytic (AI, ML, DL) process.

The Entity-Event Data Model utilized by AllegroGraph with FedShard puts core “entities” such as customers, patients, students, or people of interest at the center and then collects several layers of knowledge related to the entity as “events.” Events represent activities that transpire in a temporal context. The rich functional and contextual integration of multimodal predictive modeling and artificial intelligence is what distinguishes AllegroGraph as a modern, scalable, enterprise knowledge platform. AllegroGraph is the first big temporal Knowledge Graph technology that encapsulates a novel entity-event model to deliver a modern data architecture to the Enterprise.

Financial institutions, healthcare providers, contact centers, manufacturing firms, government agencies, and other data-driven enterprises that use AllegroGraph gain a holistic, future-proofed Knowledge Graph architecture for big data predictive analytics and machine learning across complex knowledge bases to discover deep connections, uncover new patterns, and attain explainable results.

CONTACT FRANZ INC. TODAY to build your Enterprise Scale Knowledge Graph solution.

Franz Inc.
https://franz.com