Connecting multiple systems and exchanging data among them is afrequent requirement in many business scenarios. This typically involves one or many source systems, an intermediary processor, and one or many destination systems. Some organizations invest in purpose-built solution suites such as Data Warehouse, Master Data Management (MDM), or Extract, Transform, Load (ETL) platforms, which, in-theory, cover a wider spectrum of requirements.

High cardinality is a term that often surfaces in discussions about data management and analysis. It refers to a situation where a dataset contains an unusually high number of unique values, presenting challenges when it comes to processing and analyzing the data. In this blog, we will explore the concept of high cardinality data, its implications for data analysis, and strategies for managing and analyzing it effectively.

Introduced in 2023, SwiftData is the latest addition to the range of database framework options in Swift, Apple’s primary programming language for iOS. Built on top of Core Data, two levels above SQLite, it’s great for simplifying our persistent stores and it allows us to use declarative code, which is a really useful time-saver.

Did you know that the average enterprise utilizes over 1,500 APIs to drive its digital operations? APIs play a pivotal role in today’s data-driven landscape. However, few know the impact API architecture has in enhancing API performance.

Since we launched the Open Preview of our serverless Apache Flink® service during last year’s Current, we’ve continued to add new capabilities to the product that make stream processing accessible and easy to use for everyone. In this blog post, we will highlight some of the key features added this year.

In this article, we’re diving deep into the nuts and bolts of creating a private API gateway. From the initial installation to securing your API with keys and roles, we’ll walk you through every step of the process. Whether you’re looking to connect to a Microsoft SQL Server database or any other popular database, DreamFactory makes it a breeze, automating the tedious parts and letting you focus on what matters most: your data.

Here at SmartBear, our motto is that quality isn’t just the goal, it’s the whole point. The software development process is intricate and dynamic, with constant changes being made to meet evolving user requirements and address defects. However, with these changes come potential risks. One of the most significant challenges in software development is ensuring that making modifications to an application does not inadvertently break existing functionality.

Today, an extensive range of websites and web applications significantly impact our daily lives and businesses. From online shopping and banking to social networks and news portals, they have become essential tools for communication, entertainment, and productivity. They streamline tasks like paying bills, booking travel, collaborating with colleagues, and even ordering groceries.

In the rapidly evolving landscape of API management, understanding the raw performance and reliability of your API gateway is not just an expectation — it's a necessity. At Kong, we're dedicated to ensuring our users have access to concrete, actionable data to guide their operational and development strategies.

In this post, we're going to explore Karpenter, the ultimate solution for Node Autoscaling. Karpenter provides a cost-effective capability to implement your Kong Konnect Data Plane layer using the best EC2 Instances Types options available for your Kubernetes Nodes. See the previous posts in this series for more on Data Plane Elasticity and Pod Autoscaling with VPA, HPA, and Node Autoscaling with Cluster Autoscaler on Amazon EKS 1.29.