Many companies find that it is not enough to simply keep up with the competition in their industry. Such well-known organizations as Amazon and Microsoft continually expand their service offerings, making it hard to compete. Innovation continues to be a huge buzzword in the software industry. Tech companies need a reliable way to provide clients with what they need most, which is service wherever and whenever they need it. One industry that does this best is the SaaS (Software as a Service) space.

SQL is one of the most widely adopted domain languages (i.e., used by over 65 percent of data scientists and analysts), which can help you access and interpret valuable data from AWS Redshift. As a modern-day decision-maker, AWS Redshift and SQL are vital components that drive your SDK. Through PostgreSQL, you can make data-based decisions with Amazon Redshift while minimizing the overall cost of your operations.

AWS Redshift and RDS are two different database products that AWS offers. If you're not sure which one is right for you, there are a few essential questions to answer before making your decision. This article will explore the differences between these two products and help determine which one would be best for your needs. We'll also take a look at how much it costs to use each product so that you can compare them side-by-side and see what's most affordable for your business.

The road to the data-driven enterprise is not for the faint of heart. The continuous waves of data pounding into ever-complex hybrid multicloud environments only compound the ongoing challenges of management, governance, security, skills, and rising costs, to name a few. But Hitachi Vantara has developed a path forward that combines cloud-ready infrastructure, cloud consulting and managed services to optimize applications for resiliency and performance, and automated dataops innovations.

Although many enterprises are at varying stages in their cloud journeys, most are adopting distributed mixes of on-premises and public cloud environments in order to maintain certain data and applications close by, while making others more accessible and available online. With such distributed cloud networks, core tenants of the enterprise, such as management, scalability and security, become increasingly challenging. There is a path forward, however.

Today’s applications run on data. Customers value applications not only for the functionality they provide, but also for the data itself. It may sound obvious, but without data, apps would provide little to no value for customers. And the data contained in these applications can often provide value beyond what the app itself delivers. This begs the question: Could your customers be getting more value out of your application data?

In this episode of Kongcast, Matt Stratton, a staff developer advocate at Pulumi, explains the history of configuration automation, the world of cloud engineering and how it compares to DevOps. Check out the transcript and video from our conversation below, and be sure to subscribe to get email alerts for the latest new episodes. Viktor: So before we jump to this one, tell us a bit about yourself. Matt: I spent about two decades working in traditional technology operations. I was a sysadmin.

Amazon uses a lot of adjectives to describe its cloud data warehouse: AWS Redshift is "fast," "simple" and "cost-effective." It's also popular. GE, McDonald's, Bosch, Coca Cola, and countless other brands, ranging from startups to Fortune 500 companies, have added Redshift to their tech stacks. But why is AWS Redshift used? And why is it the world's No.1 cloud data warehouse? Below, learn more about what Redshift does, how it does it, and why it could be a great fit for your organization.

When CTO James Dixon coined the term “data lake” in 2011, he imagined a single storage repository where organizations could store both structured and unstructured data in their raw format until it was needed for analytics. But without the right storage technology, data governance, or analytical tools, the first data lakes quickly became “data swamps” - morasses of data with no organizational structure and no efficient way to access or extract meaningful insights.

Amazon Redshift says it executes data operations ten times faster than other enterprise data warehouses because of a hardware-accelerated cache called Advanced Query Accelerator (AQUAD). It also claims three times better price-performance than other similar technologies. Statements like these are what make Redshift an attractive option for companies that want to push data into a warehouse for analytics.