From Data Warehouse to Data Mesh: Usable Data is Still Key
A data mesh flips the script on centralization and having a monolithic data structure by decentralizing data management to the various business domains across …
This big data technology lets users query a continuous data stream and detect conditions — within a few milliseconds to minutes — after receiving that data (i.e. flow of events); processing data in motion, or computing on data directly as it’s produced or received.
A data mesh flips the script on centralization and having a monolithic data structure by decentralizing data management to the various business domains across …
Organizations are increasingly opting for an analyze-then-store method for streaming data, according to a new survey by
As the need for real-time data expands, organizations will need to operate all three of these meshes at internet scale with enterprise-grade capabilities.
A discussion of the benefits Apache Pulsar brings versus other streaming technologies, and how companies are using it.
A semantic layer lets organizations connect data warehouses, data lakes, and data lakehouses to an existing data ecosystem to ensure their continued relevance …
Organizations are using event-driven architectures, Apache Kafka, Apache Pulsar, and other streaming technologies to handle the glut of event messages they …
Harnessing data streams — joining both batch and real-time events — empowers data scientists and analysts to address sophisticated
Why Apache Pulsar is the right choice for multi-datacenter, geo-distributed
Continuous intelligence can offer a unified view of many diverse security systems. And it helps to bring some level of simplicity to the complexity that …
The initial goal for Pulsar was to create a multi-tenant scalable messaging system that could serve as a unified platform for a wide variety of demanding use …