ray vs tfjs
ray and tfjs share 15 technologies: h5py, werkzeug, React, prompt-toolkit, Rich, ml-dtypes, opt-einsum, orbax-checkpoint, tf-keras, TensorFlow, jax, flax, Keras, markdown, and markupsafe. ray is written in Python and tfjs in TypeScript.
What they share and what sets them apart
ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python44.2kRead on November 6, 2026, at commit 77567c5What is ray built with?Only in ray
- FastAPI
- amqp
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- diskcache
expiringdict
- gitdb
google-cloud-core
kombu
pickleshare
- pylance
- pymongo
pyarrow
- aioboto3
- MongoDB
- Redis
- adlfs
- smart-open
pyiceberg
- pymysql
clickhouse-connect
deltalake
- gcsfs
- Celery
- fastavro
- pyzmq
- s3fs
webdataset
- Hugging Face
- Google Cloud Storage
- Kafka
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
- Ray
starlette
- AIOHTTP
- Lightning
- anyio
tornado
uvicorn
react-router-dom
- alabaster
- cycler
fonttools
jupyterlab-pygments
- pydata-sphinx-theme
- soupsieve
- sphinx-design
- tinycss2
contourpy
- glfw
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
pyopengl
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
matplotlib
- pydot
- alembic
peewee
sqlglot
- SQLAlchemy
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
google-auth-oauthlib
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
requests-oauthlib
- cryptography
google-auth-httplib2
- albucore
- bitsandbytes
cmdstanpy
- crcmod
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
gradio-client
- gym
- LangChain
- llvmlite
lm-eval
- MLflow
nltk
- ONNX
- onnxruntime
onnxscript
openai-whisper
peft
prophet
rouge-score
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
- tiktoken
timm
tokenizers
torchtext
- triton
gymnasium
- torch
- transformers
torchvision
- xgboost
lightgbm
- scikit-learn
accelerate
- datasets
- pytorch-lightning
evaluate
- torchmetrics
albumentations
deepspeed
diffusers
- hyperopt
- Optuna
- pettingzoo
tensordict
tensorflow-datasets
tensorflow-probability
torchaudio
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
markdown-it-py
- mdurl
mistune
- moviepy
- nbconvert
- nh3
- openpyxl
- pandocfilters
ruamel-yaml
webencodings
- xlrd
- xmltodict
pillow
- docutils
- jinja2
- beautifulsoup4
av
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-specifications
- pathvalidate
- pydantic-core
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- validators
- Pydantic
- jsonschema
- openapi-schema-validator
- aiobotocore
- azure-mgmt-compute
- azure-mgmt-resource
- colorlog
- Gunicorn
- opentelemetry-api
opentelemetry-instrumentation
opentelemetry-semantic-conventions
- python-json-logger
psutil
- boto3
- botocore
prometheus-client
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
In common
h5py
werkzeug
- React
prompt-toolkit
- Rich
- ml-dtypes
- opt-einsum
- orbax-checkpoint
tf-keras
- TensorFlow
jax
flax
- Keras
- markdown
markupsafe
tfjs
A WebGL accelerated JavaScript library for training and deploying ML models.
TypeScript19.2kRead on November 6, 2026, at commit 7f5309fWhat is tfjs built with?Only in tfjs
- tensorboard-data-server
@react-native-async-storage/async-storage
react-native
- Preact
- jaxlib
- optax
- tensorflow-io-gcs-filesystem
- tensorflow-hub
- progress
- expo-gl
- expo-camera
- jpeg-js
- glamor
vega-embed
d3-selection
vega-lite
Side by side
Frequently asked questions
Which is bigger, ray or tfjs?
The proof: ray-project/ray's code at commit 77567c5
Which has more GitHub stars, ray or tfjs?
The proof: ray-project/ray on GitHub
Which has more tests, ray or tfjs?
The proof: ray-project/ray's code at commit 77567c5
Which was updated more recently, ray or tfjs?
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, ray or tfjs?
See inside your code, today.
Paste your repo and see it drawn, part by part: a medium one in under a minute.
Free, no account.

