Top 6 Cloud Data Warehouses in 2023

1

Google BigQuery

You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive dashboard using the BigQuery BI engine.

#Data Management #Data Warehousing #Data Dashboard 35 social mentions

2

Amazon Redshift

Coined in November 2021, Amazon Redshift was launched as a fully managed cloud data warehouse that can handle petabyte-scale data. While it was not the first cloud data warehouse, it became the first to proliferate in the market share after a large-scale adoption. Redshift uses SQL dialect based on PostgreSQL, which is well-known by many analysts globally, and its architecture resembles that of on-premise data warehouses.

#Big Data #Databases #Relational Databases 26 social mentions

3

Snowflake

Snowflake accommodates data analysts of all levels since it does not use Python or R programming language. It is also well known for its secure and compressed storage for semi-structured data. Besides this, it allows you to spin multiple virtual warehouses based on your needs while parallelizing and isolating individual queries boosting their performance. You can interact with Snowflake using a web browser, the command line, analytics platforms, and other supported drivers.

#Data Warehousing #Cloud Data #Data Dashboard 4 social mentions

4

Microsoft Azure SQL Database

The Azure SQL database is prominent for cloud-based hosting with an interactive user journey from creating SQL servers to configuring databases. It is also widely preferred because of its easy-to-use interface and many functionalities for manipulating data. Also, it is scalable to reduce costs and optimize performance on low usage.

#Databases #Relational Databases #NoSQL Databases 2 social mentions

5

Azure Synapse Analytics

Azure Synapse analytics is scalable for large data tables based on its distributed computing. It relies on the MPP (mentioned in the beginning, revisit if you did not grasp it) to quickly run high volumes of complex queries across multiple nodes. With Synapse, there’s an extra emphasis on security and privacy.

#Office & Productivity #Development #Data Science And Machine Learning 3 social mentions

6

Firebolt

While still new to the field. Firebolt claims to be a future-generation warehouse performing 182 times faster than that SQL-based systems. Firebolt is fast since it uses new data parsing and compressing techniques.

#Data Management #Cloud Computing #Cloud Data Services