Dremio has introduced new capabilities to deliver sub-second query response times directly on cloud data lakes and support for thousands of concurrent users and queries.
Dremio today announced its Fall 2020 release, which brings the capability referenced above. Users can now query data sitting in Amazon’s S3 and Microsoft’s ADLS directly from a BI tool like Looker, Tableau, or PowerBI.
Dremio today announced ground-breaking innovations that deliver sub-second query response times directly on cloud data lakes.
Here is the list of the Big Data 50—Companies Driving Innovation in 2020
The separation of storage, data, and compute provides greater agility, stability, and speed to insight.
TDWI article that explains the ten mistakes to avoid when querying data lakes, focusing on effective best practices for keeping data in data lake storage and querying it directly, thereby raising productivity and efficiency and lowering costs and complexity.
Dataversity article on cloud data lakes vs. cloud data warehouses.
The separation of storage, data, and compute provides greater agility, stability, and speed to insight.
Users at the Dremio-sponsored Subsurface virtual conference detail data lake efforts and trends, including the emerging Apache Iceberg project, originally created by Netflix.
Big data and analytics funding rounds are increasingly common in what has become a very competitive vendor landscape. Here is the list of the top big data and analytics funding rounds so far in 2020.
TFIR interview with Jason Nadeau on the risks of data warehouses
Big data and analytics funding rounds are increasingly common in what has become a very competitive vendor landscape. Here is the list of the top big data and analytics funding rounds so far in 2020.
Analytics matter most when they’re delivered quickly. In today’s business climate, that latency can be very small. Just how fast?
New features in the AWS Edition of Dremio’s data lake engine make it easier for organizations to scale and manage data lake queries in the cloud.
Cloud Data Lakes are growing as data-heavy enterprises take advantage of lower cost, faster time to insight, efficiency, and agility.
