Systems | Development | Analytics | API | Testing

A 2021 Educase report shows that 75% of surveyed institutions have started or are planning extensive digital transformation strategies to improve their data utilization. The importance of a strategic approach to data utilization in this context cannot be overstated. Effective data management frameworks ensure that data across the institution is accurate, consistent, and used in alignment with internal policies and external regulations.

Data ingestion is important in collecting and transferring data from various sources to storage or processing systems. In this blog, we compare the best data ingestion tools available in the market in 2024. We will cover their features and pros and cons to help you select the best software for your use-case.

Ruby on Rails is the most popular web framework in the Ruby ecosystem and has a large user base, ranging from freelancers to large established companies. With an active user community and wide-ranging documentation, it can be used to build everything from simple applications to complex web platforms. That said, a new contestant is taking on Rails’ dominance for the full-stack Ruby framework title: Hanami.

Hey there! At Koyeb, we really like diving into technical stuff. But here’s the thing: not every cool thing we stumble upon or think about needs a massive blog post. And honestly, not everything we’re into is directly related to what Koyeb does or about infrastructure in general. So, we’ve got an idea: what if we start sharing these bits and pieces with you in a series of really short blog posts?

Building top-tier enterprise-grade intelligence using LLMs has traditionally been prohibitively expensive and resource-hungry, and often costs tens to hundreds of millions of dollars. As researchers, we have grappled with the constraints of efficiently training and inferencing LLMs for years.