Vertica claims to offer the "most advanced unified analytical warehouse" in the world, providing actionable data insights you can't find anywhere else. The truth is, like any data warehouse, Vertica is only as good as the data you put into it. Moving data to Vertica can be a headache for organizations without a data engineering team. Data might live in various locations — transactional databases, relational databases, customer relationship management (CRM) systems, you name it.

Amazon Redshift makes it easier to uncover transformative insights from big data. Analytical queries that once took hours can now run in seconds. Redshift allows businesses to make data-driven decisions faster, which in turn unlocks greater growth and success. For a CTO, full-stack engineer, or systems architect, the question isn’t so much what is possible with Amazon Redshift, but how. How do you ensure optimal, consistent runtimes on analytical queries and reports?

BigQuery is a powerful tool for data analytics and business intelligence, but it isn't very easy to get the most out of it without some help from ETL (extract, transform, load). In this blog post, we'll go over some of the best ETL solutions for BigQuery to help you make sense of your company's data.

When it comes to providing the latest and greatest ETL and ELT tools, the platforms Stitch, Fivetran, and Xplenty are all top contenders. That being said, each platform also has its own set of pros and cons. Ultimately, the best ETL/ELT platform for your company will largely depend upon the needs of your organization. So, which platform will reign supreme for your company in the Stitch vs Fivetran vs Xplenty matchup?

Heroku leverages the open-source technology of PostgreSQL to deliver a powerful and reliable database-as-a-service solution. Heroku Postgres acts as both a source and destination for data integration. With native support for a variety of programming languages and features that ensure security and compliance, it is a top resource for many companies. What do you need to know about Heroku, and what tools should you use to perform ETL (extract, transform and load) and ELT (extract, load and transform)?

Choosing the right ETL solution for your business is essential, but how do your compare each option? Learn how to compare each potential ETL provider and discover what attributes and features stand out from one another and how that can benefit certain business endeavors.

ETL (extract, transform, load) is the backbone of modern data integration, efficiently migrating massive quantities of information into a data warehouse like Snowflake. But with so many Snowflake ETL tools on the market these days, how can you choose the best for migrating your data? Below we’ll discuss our favorite Snowflake ETL tools, including their pros, cons, and user reviews so that you can make the choice that’s right for your situation.

Mulesoft is an all-inclusive data and application integration platform owned by Salesforce. It offers many types of functionality, including Extract, Transform, Load (ETL), API management, and Integration Platform as a Service (IPaaS). Mulesoft may offer a broad range of capabilities, but it has a challenging learning curve, a high price point, and may be far more than what your organization needs for data transformation.

So you want to move data to Amazon Redshift? You're not the only one. Every day, thousands of organizations worldwide migrate data to Redshift, which Amazon claims is the world's fastest cloud data warehouse. These organizations have one mission: To move data to Redshift so they can generate business intelligence (BI) from the latest metrics. Amazon's data warehouse makes it easy to produce metrics that power data-driven organizations like yours.

Managed data integration is the best way for enterprises to get maximum value from their data — and their data engineering teams.