s someone who works remotely, I've tried my fair share of collaboration apps. However, I have to say that Microsoft Teams has impressed me the most. It's a comprehensive app that brings together all the tools I need to communicate and collaborate with my colleagues seamlessly.
The interface of Microsoft Teams is user-friendly and easy to navigate. I particularly love the left-hand navigation bar that provides quick access to all the features, including chats, meetings, files, and activity. The app integrates with other Microsoft apps, such as Outlook and OneDrive, making it easier to schedule meetings and access files. The chat feature is simple, yet effective, with options to create groups, share files, and use emojis and GIFs.
Based on our record, Apache Thrift seems to be more popular. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / 5 months ago
Services in general communicate via Thrift (and in some cases HTTP). Source: over 1 year ago
Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: over 1 year ago
RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 1 year ago
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago
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