Developers often build high-performing, scalable applications using GraphQL and PostgreSQL to define data structure and achieve reliability, scalability, and high performance. First, however, selecting the appropriate framework to simplify and streamline the development process is crucial while building a GraphQL API with PostgreSQL. This blog will explore the top tools for building GraphQL APIs with PostgreSQL, including Hasura, Postgraphile, Prisma, and GraphQL Nexus.

CIOs are fed up with having a plethora of BI and analytics tools with business units seemingly chasing the shiniest new solution. And although most industry surveys show data and analytics budgets continuing to grow despite a faltering economy, there is closer scrutiny and belt tightening to rid teams of overlapping capabilities. Here’s a look at how BI tool portfolios have become such a mess and how to streamline them.

Cloudera SQL Stream builder gives non-technical users the power of a unified stream processing engine so they can integrate, aggregate, query, and analyze both streaming and batch data sources in a single SQL interface. This allows business users to define events of interest for which they need to continuously monitor and respond quickly. A dead letter queue (DLQ) can be used if there are deserialization errors when events are consumed from a Kafka topic.

In the article “From Data to Insights: An Introduction to Product Analytics”, we walk you through the basics of product analytics, providing you with a high-level approach to get started with it. This time, we’d like to dig in deeper to dissect every step of the product analytics process, assuming that the main goal is to improve user engagement and retention.

Much like Apple people tend to be all Apple, all the time, Microsoft Dynamics ERP users tend to prefer Microsoft products for all their computing needs. It’s not hard to understand why. Using products from the same ecosystem prevents compatibility issues and saves time in learning multiple systems.

Many years have passed since the first testing methodology made its way into SDLC processes. At the time, the software testing activities were simple and straightforward: validating the application against user requirements after the development stage was over. The times moved ahead, and the procedures evolved. Today, several testing types exist under the umbrella term of ‘software testing.’ Two of them are scripted testing and exploratory testing.

Good data is the foundation of any successful business. Forecasting, planning, or tracking a company’s long-term performance is difficult without good data. Real-time information provided by data supports decision-making and helps save time and money. So, it becomes essential to test the data better to draw accurate insights.

Do you understand JavaScript's concurrency model? This article is here to help! Learn how JavaScript executes non-blocking functions and dive into event loops, callbacks, async/await, and promises.

Fivetran partners with Databricks on their launch of Lakehouse for Manufacturing (L4M)

Imagine you’re driving a car with the engine roaring, the wheels spinning, and the wind blowing through your hair. Everything might seem perfect until you step on the brakes, and it takes 10 full seconds to bring the car to a stop. Conducting thorough testing can help detect such flaws. Non-functional testing, here, will help test the braking system’s response time, how well it works, how effective it is, its performance, and so on.