Cloudera

FEBRUARY 9, 2021

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.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Cloudera

SEPTEMBER 15, 2022

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?

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Cloudera

SEPTEMBER 1, 2020

DDE is a new template flavor within CDP Data Hub in Cloudera’s public cloud deployment option (CDP PC). It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. For the examples presented in this blog, we assume you have a CDP account already. What does DDE entail?

Cloud Storage 67

Cloud Storage Unstructured Data AWS Analytics Application 67

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

AltexSoft

OCTOBER 21, 2022

A single cluster can span across multiple data centers and cloud facilities. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Depending on the type of deployment (cloud or on-premise), cluster size, and the number of integrations, the deployment may take days to weeks to even months.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

MARCH 15, 2021

This will avoid unnecessary processing during data ingestion and reduce the storage bloat due to redundant data. The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e., and your solution will only be able to provide valuable real-time analytics if you are able to meet them.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. If your database is cloud-based, using SQL to clean data is far more effective than scripting languages.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52