The main video-streaming trend for developers is not a universal shift to the newest protocol or the lowest possible latency. HLS and DASH remain core choices for internet delivery; low-latency designs make sense when interaction demands them; and AV1 can improve compression, but only when devices can decode it well. Choose around the job your stream must do: its latency target, audience scale, network resilience, device support, quality needs, and operating cost.
Which streaming foundations still matter?
HLS and MPEG-DASH continue to support live and on-demand delivery over HTTP. They use ordinary web servers and CDNs, and adaptive playback can adjust to available network conditions. For broad internet distribution, that foundation remains useful; a newer protocol is not automatically a better fit.
HLS
Apple describes HLS as a live and on-demand delivery technology that adapts playback to network conditions. Its developer hub includes current HLS material, low-latency documentation, examples, a stream validator, and developer forums. Apple’s concise description is: “HLS is designed for reliability and dynamically adapts to network conditions by optimizing playback for the available speed of wired and wireless connections.”
MPEG-DASH
DASH is another HTTP-based adaptive streaming format for live and on-demand delivery. ISO lists the sixth edition, ISO/IEC 23009-1:2026, as published in July 2026. Its scope includes formats for the Media Presentation Description and media segments used for adaptive delivery of MPEG media over HTTP. MPEG also points implementers to conformance software and implementation guidance.
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These standards are not competing answers to every streaming problem. Start by defining the delivery job, then assess which format, player ecosystem, and infrastructure suit it.
When is low latency worth the trade-off?
Low latency matters when viewers need to react, communicate, or control something in near real time. A conversational game feature or live interaction may have different needs from a large audience watching a broadcast. Set a latency target from the use case rather than treating “as low as possible” as a universal requirement.
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HTTP-based low-latency delivery
LL-HLS and LL-DASH can use CMAF chunks to reduce latency without tying it as tightly to the duration of a complete media segment. These approaches preserve an HTTP-based delivery model, but lowering delay can bring trade-offs: higher costs, less flexibility in bitrate or resolution adaptation, and greater exposure to visible disruption when network conditions fluctuate. These operational considerations are described in IETF RFC 9317, “Operational Considerations for Streaming Media.”
Real-time transport
For conversational or interactive use with especially tight feedback requirements, real-time approaches such as RTP and WebRTC are relevant. For broad live distribution, HTTP-based delivery may fit better. There is no universal latency ranking that decides the architecture: interaction needs, audience scale, and resilience requirements matter together.
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Questions to settle before choosing
- Latency target: What delay can the experience tolerate, and what user action depends on it?
- Audience scale: Is the system serving a large viewing audience, a real-time conversation, or a mixture?
- Network resilience: How much buffering and adaptation can the experience tolerate, and what happens during transient network variation?
- Quality and bitrate: Which resolutions and bitrates matter, and how do those requirements interact with the latency target?
- Device and codec coverage: Can the target devices decode the formats you plan to deliver acceptably?
- Operating cost and complexity: What additional infrastructure and operational work are justified by the experience?
Is AV1 ready for a streaming app?
AV1 is a viable option to evaluate, not a guarantee of better results on every device or workload. Meta’s September 2025 article, summarizing a joint white paper with Vodafone and Google, says the companies found AV1 can improve compression by 30% compared with H.264 and VP9. Treat that as a reported finding, not a universal result for every encoder, content type, or deployment.
Device support is part of the decision. Meta’s article recommends evaluating hardware AV1 decoding and considering software decoding where hardware decoding is unavailable. It also reports that many lower- and mid-tier phones in use lack hardware codec support. A codec’s compression advantage only helps if a viewer’s device can decode it acceptably within the app’s performance and latency constraints.
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Real-time AV1 adds more variables
In its June 22, 2026 account of adopting AV1 for real-time communication, Meta describes trade-offs between quality and low latency. Multi-pass encoding can add delay, buffering can increase latency, and bitrate spikes can freeze calls. Its described deployment approach combines a low-complexity encoder, machine-learning-based device eligibility, adaptive codec switching, and error resilience.
That account illustrates the implementation work behind real-time codec deployment: device eligibility and fallback behavior are architecture concerns, not details to assume away. Test quality, latency, and stability together under representative device and network conditions.
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What do recent low-latency surveys actually show?
Bitmovin’s 2024–2025 Video Developer Report lists LL-HLS at 34.8%, LL-DASH at 23.9%, WebRTC at 22.8%, and 42.4% of respondents as not using low-latency streaming. These figures describe that report’s respondents, not representative global market share. The report also notes that respondents reported varied latency ranges and that low latency should be prioritized only when a use case demands it.
The Streaming Video Technology Alliance’s SVTA7111 Low Latency Survey Report collected responses from January through July 2025 and calls its findings directional because participation was self-selected. It covers how respondents define and measure latency, current and target latency, protocol use, cloud versus on-premises deployment, and perceived barriers. Read both surveys as snapshots of participating developers’ and organizations’ reported practices, not as a census of the industry.
How should a team make the architecture decision?
Compare designs against the same use case rather than choosing by protocol name or codec efficiency alone. The IETF’s account of low-latency trade-offs and Meta’s AV1 deployment examples show why performance, resilience, device coverage, and operational effort need to be considered together.
| Decision axis | What to establish | Why it changes the choice |
|---|---|---|
| Latency | Required end-to-end delay and which interactions depend on it | Lower latency can raise delivery cost and reduce robustness. |
| Scale | Expected audience and whether the experience is broadcast, interactive, or both | Ultra-low-latency interaction and mass live distribution do not necessarily scale the same way. |
| Resilience | Acceptable buffering, adaptation behavior, and response to transient network variation | Shorter delivery paths and less buffering can expose viewers more readily to network problems. |
| Devices and codecs | Target device capabilities, hardware decoding availability, and fallback needs | Codec efficiency is useful only when target devices can decode the format acceptably. |
| Quality and bitrate | Required picture quality, bitrate range, and their interaction with the latency target | Codec, encoding, buffering, and latency decisions affect one another. |
| Cost and complexity | Infrastructure, implementation, and operational effort justified by the experience | Low-latency delivery and broad device coverage can add operational work and cost. |
For a different job: keeping prerecorded video live on YouTube
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