OpenCV Solution

According to this source, you can set the buffersize of a cv::VideoCapture object.

cv::VideoCapture cap;
cap.set(CV_CAP_PROP_BUFFERSIZE, 3); // internal buffer will now store only 3 frames

// rest of your code...

There is an important limitation however:

CV_CAP_PROP_BUFFERSIZE Amount of frames stored in internal buffer memory (note: only supported by DC1394 v 2.x backend currently)

Update from comments. In newer versions of OpenCV (3.4+), the limitation seems to be gone and the code uses scoped enumerations:

cv::VideoCapture cap;
cap.set(cv::CAP_PROP_BUFFERSIZE, 3);

Hackaround 1

If the solution does not work, take a look at this post that explains how to hack around the issue.

In a nutshell: the time needed to query a frame is measured; if it is too low, it means the frame was read from the buffer and can be discarded. Continue querying frames until the time measured exceeds a certain limit. When this happens, the buffer was empty and the returned frame is up to date.

(The answer on the linked post shows: returning a frame from the buffer takes about 1/8th the time of returning an up to date frame. Your mileage may vary, of course!)

Hackaround 2

A different solution, inspired by this post, is to create a third thread that grabs frames continuously at high speed to keep the buffer empty. This thread should use the cv::VideoCapture.grab() to avoid overhead.

You could use a simple spin-lock to synchronize reading frames between the real worker thread and the third thread.

Whether CAP_PROP_BUFFERSIZE is supported appears quite operating system and backend-specific. E.g., the 2.4 docs state it is "only supported by DC1394 [Firewire] v 2.x backend currently," and for backend V4L, according to the code, support was added only on 9 Mar 2018.

The easiest non-brittle way to disable the buffer is using a separate thread; for details, see my comments under Piotr Kurowski's answer. Here Python code that uses a separate thread to implement a bufferless VideoCapture: (I did not have a opencv4nodejs environment.)

import cv2, Queue, threading, time

# bufferless VideoCapture
class VideoCapture:

  def __init__(self, name):
    self.cap = cv2.VideoCapture(name)
    self.q = Queue.Queue()
    t = threading.Thread(target=self._reader)
    t.daemon = True
    t.start()

  # read frames as soon as they are available, keeping only most recent one
  def _reader(self):
    while True:
      ret, frame = self.cap.read()
      if not ret:
        break
      if not self.q.empty():
        try:
          self.q.get_nowait()   # discard previous (unprocessed) frame
        except Queue.Empty:
          pass
      self.q.put(frame)

  def read(self):
    return self.q.get()

cap = VideoCapture(0)
while True:
  frame = cap.read()
  time.sleep(.5)   # simulate long processing
  cv2.imshow("frame", frame)
  if chr(cv2.waitKey(1)&255) == 'q':
    break

The frame reader thread is encapsulated inside the custom VideoCapture class, and communication with the main thread is via a queue.

This answer suggests using cap.grab() in a reader thread, but the docs do not guarantee that grab() clears the buffer, so this may work in some cases but not in others.