Monte Carlo

APRIL 24, 2023

AWS is one of the most popular data lake vendors. AWS Lake Formation offers an alternative for data teams looking for a more structured data lake or data lakehouse solution. This is a lot of work and for most companies, it takes them several months to set up a data lake.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Ascend.io

AUGUST 31, 2023

There are a range of tools dedicated to just the extraction (“E”) function to land data in any type of data warehouse or data lake. Once in place, any transformations on the data are performed directly in the data lake on demand as different analytical tasks come up.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Towards Data Science

MARCH 5, 2024

BigQuery separates storage and compute with Google’s Jupiter network in-between to utilize 1 Petabit/sec of total bisection bandwidth. The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google.

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

ProjectPro

JANUARY 24, 2023

Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources. BigQuery is a highly scalable data warehouse platform with a built-in query engine offered by Google Cloud Platform. What is Google BigQuery Used for?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data. Examples include Amazon DynamoDB and Google Cloud Datastore.

Database 52

Database NoSQL Management Relational Database 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52