Zero Overhead Pub/sub, Store/Query and Compute.
zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
First class abstractions for pub/sub, storage, query, and evals simplify the development of distributed applications, at any scale.
Pub/Sub
zenoh provides efficient publish/subscribe primitives, supporting
multiple levels of reliability, dynamic discovery, fragmentation, and
wire-level batching.
Storage and Queries
zenoh provides primitives for defining geo-distributed storages as well
as well defined semantics for quering and aggregating.
Evaluations
zenoh allows applications to register computations that will be
triggered by queries. A simple mechanism that allows many pattern
to be implemented, such as RPC and map-reduce.
The zenoh protocol and its implementations can scale-out as well as scale-down.
Scalable Routing
zenoh provides scale-out through a scalable routing infrastructure
that allows your applications to be deployed at Internet scale.
Low Power Networks
zenoh has been designed to run across extremely constrained transports
such as LPWAN and LowPAN. To maximise the usable bandwidth, zenoh can run
on OSI Layer 2 and has a minimal wire overhead of 4 bytes.
Constrained Deviceszenoh implementations can be extremely resource constrained. Our smallest implementation takes as little as 300 bytes footprint on an Atmel 8-bit microcontroller.
zenoh is fast to learn and extremely performant.
Fast Adoption
zenoh has a very simple API that makes it extremely fast to get started
and productive. API are available for the most popular programming languages
and more are added regularly.
Low Latency
zenoh has an extremely low latency, thus it is appropriate for applications
that require extremely low overhead and reaction times.
High Throughput
zenoh delivers extremely high throughput and allow you to further
its off-the-shelf performance through the batching API.