Data Warehouses

Redshift vs BigQuery

Choosing the right data warehouse is a critical component of your general data and analytic business needs. One of the biggest questions that businesses ask when choosing their data warehouse providers is this: Should you use Snowflake, Amazon RedShift, or Google's BigQuery data warehouse for your business needs? We've already covered Amazon RedShift vs. Snowflake and Google BigQuery vs. Snowflake, but what about Amazon RedShift vs. Google BigQuery?

The Ultimate Guide to Data Warehouse Design

Data warehouses help you run logical queries, build accurate forecasting models, and identify impactful trends throughout your organization. But, what goes into designing a data warehouse? Whether you choose to utilize a pre-built vendor solution or you're starting from scratch — you'll need some level of warehouse design to successfully adopt a new data warehouse.

Redshift vs Snowflake: 6 Key Differences

About five years ago, there was plenty of hype surrounding big data and analytics. Today, the industry has mainly lived up to the hype and transformed into the underlying force that drives businesses forward. Over the years, the sheer amount of data generated every second has grown exponentially. This has led to the emergence of enterprise cloud data warehouse technology that’s highly efficient in handling analytics workloads.

9 Expert Tips for Using Snowflake

Snowflake is a robust data warehouse that has changed the data science game for many organizations. Snowflake lets you analyze your data using the most sophisticated query engine available today with its cloud-native architecture. But using Snowflake is not always as simple as using other products on the market. Below are nine expert tips to help you master the Snowflake platform.

PostgreSQL to Amazon Redshift: 4 Ways to Replicate Your Data

PostgreSQL is the preferred platform of millions of developers around the world. The open-source tool is one of the most powerful databases on the planet, with the ability to handle sophisticated analytical workloads and high levels of concurrency. That makes PostgreSQL (also called Postgres) a popular DB for scientific research and AI/ML projects. It’s also a popular production database for data-driven companies in every industry. But no database is perfect.

Redshift Join: How to use Redshift's Join Clause

Redshift’s JOIN clause is perhaps the second most important clause after SELECT clause, and it is used even more ubiquitously, considering how interconnected a typical application database’s tables are. Due to that connectivity between datasets, data developers require many joins to collect and process all the data points involved in most use cases. Unfortunately, as the number of tables you’re joining in grows, so does the sloth of your query.

How to migrate an on-premises data warehouse to BigQuery on Google Cloud

Data teams across companies have continuous challenges of consolidating data, processing it and making it useful. They deal with challenges such as a mixture of multiple ETL jobs, long ETL windows capacity-bound on-premise data warehouses and ever-increasing demands from users. They also need to make sure that the downstream requirements of ML, reporting and analytics are met with the data processing.

What is Amazon Redshift Spectrum?

Amazon S3 (Simple Storage Service) has been around since 2006. Most use this scalable, cloud-based service for archiving and backing up data. Within 10 years of its birth, S3 stored over 2 trillion objects, each up to 5 terabytes in size. Enterprises value their data as something worth preserving. But much of this data lies inert, in “cold” data lakes, unavailable for analysis. Also called “dark data”, it can hold key insights for enterprises.

AWS Redshift Pricing: How much does Redshift cost?

While Redshift is arguably the best data warehouse on the market, it can come with a hefty price tag. We’ve created this Redshift pricing guide to help you evaluate Redshift cheaply, create a budget for full implementation, and optimize your Redshift set up so that you’re getting the most bang for your data buck. Ready to get started? Think of this blog post as a “choose your own adventure” guide.