Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Srs | 21,104 | a day ago | 93 | September 16, 2022 | 183 | mit | C++ | |||
SRS is a simple, high efficiency and realtime video server, supports RTMP, WebRTC, HLS, HTTP-FLV, SRT, MPEG-DASH and GB28181. | ||||||||||
Node Fetch | 8,220 | 219,668 | 25,410 | 3 days ago | 86 | July 31, 2022 | 172 | mit | JavaScript | |
A light-weight module that brings the Fetch API to Node.js | ||||||||||
Node Spdy | 2,725 | 292,166 | 386 | 3 years ago | 212 | April 04, 2020 | 62 | JavaScript | ||
SPDY server on Node.js | ||||||||||
Piping Server | 2,671 | 2 | 13 hours ago | 106 | September 04, 2022 | 15 | mit | TypeScript | ||
Infinitely transfer between every device over pure HTTP with pipes or browsers | ||||||||||
Aleph | 2,467 | 521 | 3 days ago | 117 | February 21, 2019 | 19 | mit | Clojure | ||
Asynchronous communication for Clojure | ||||||||||
Cinatra | 1,503 | 6 days ago | 74 | mit | C++ | |||||
modern c++(c++20), cross-platform, header-only, easy to use http framework | ||||||||||
Squbs | 1,381 | 6 | a year ago | 12 | January 18, 2021 | 69 | apache-2.0 | Scala | ||
Akka Streams & Akka HTTP for Large-Scale Production Deployments | ||||||||||
Embedio | 1,301 | 33 | 26 | 3 months ago | 153 | March 11, 2020 | 40 | other | C# | |
A tiny, cross-platform, module based web server for .NET | ||||||||||
Ustreamer | 1,202 | 7 days ago | 19 | gpl-3.0 | C | |||||
µStreamer - Lightweight and fast MJPEG-HTTP streamer | ||||||||||
Download | 1,147 | 43,052 | 1,568 | a year ago | 73 | April 02, 2020 | 56 | mit | JavaScript | |
Download and extract files |
This application reads from an existing Kafka topic from the earliest offset and streams the response over HTTP with the help of Server-Sent Events.
Create a topic and publish some data on it.
Perform GET /streaming-kafka/<topicName>
in order to see the data that
is published on the Kafka topic. Note that it is an infinite streaming
response so any newly published data on the Kafka topic will continue
showing up in the streaming response.
Note: I use the same consumer group so if two users hit the same endpoint then only one user may see all the data or both users may see only some part of the data due to how the consumer group binds each consumer to partitions in the topic.