Remove Analytics Application Remove Blog Remove Cloud
article thumbnail

Handling Bursty Traffic in Real-Time Analytics Applications

Rockset

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Finally, the database must be cloud native, so all scaling is automatic and hidden from developers and users. For more details, read my blog post on ALT and why it beats the Lambda architecture for real-time analytics.

article thumbnail

Azure Databricks: A Comprehensive Guide

Analytics Vidhya

Introduction Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform that is built on top of the Microsoft Azure cloud. In this blog post, we will take a closer look at Azure Databricks, its key features, […] The post Azure Databricks: A Comprehensive Guide appeared first on Analytics Vidhya.

Big Data 310
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Octopai Acquisition Enhances Metadata Management to Trust Data Across Entire Data Estate

Cloudera

Combining Octopai capabilities with Cloudera’s AI powered hybrid data platform provides deeper data understanding, enhanced security, and robust data governance – essential for driving AI and analytics success. This will also accelerate deployment of new data products for AI, gen AI, and analytics applications.

article thumbnail

Apache Ozone – A Multi-Protocol Aware Storage System

Cloudera

Navigating this intricate maze of data can be challenging, and that’s why Apache Ozone has become a popular, cloud-native storage solution that spans any data use case with the performance needed for today’s data architectures. Most traditional analytics applications like Hive, Spark, Impala, YARN etc.

Systems 103
article thumbnail

A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1

Cloudera

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Cost-Effective.

article thumbnail

Altus SDX: Shared services for cloud-based analytics

Cloudera

People are gravitating to the analytics services of the large public cloud providers because the “house-brand” offerings seem to be the easiest choice. This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications.

Cloud 40
article thumbnail

Demystifying Modern Data Platforms

Cloudera

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Ramsey International Modern Data Platform Architecture. What is a data mesh?