ray vs fiftyone
ray and fiftyone share 19 technologies: pyarrow, mcap, Hugging Face, werkzeug, React, pydata-sphinx-theme, sphinx-design, Plotly, ipywidgets, torch, transformers, TensorFlow, torchvision, markupsafe, myst-parser, docutils, jinja2, MUI, and @mui/icons-material. ray is written in Python and fiftyone 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.
Python44.3kRead on November 13, 2026, at commit de4c576What is ray built with?Only in ray
- FastAPI
- aimrecords
- aimrocks
- amqp
- array-record
- arro3-core
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- delta-kernel-rust-sharing-wrapper
- diskcache
expiringdict
- feather-format
- gitdb
google-cloud-core
h5py
- huey
jupyter-cache
kombu
- partd
petastorm
pickleshare
- py-partiql-parser
- pylance
- pymongo
- qpd
- s3torchconnectorclient
- s3transfer
- semidbm
- sqlitedict
taskiq
tensorboard-data-server
- zict
- aioboto3
- MongoDB
- Redis
- adlfs
pyiceberg
- smart-open
clickhouse-connect
daft
deltalake
- gcsfs
lance-namespace
- obstore
- Celery
delta-sharing
- fastavro
hudi
- pyzmq
- s3fs
- s3torchconnector
- taskiq-redis
zarr
- Google Cloud Storage
- Kafka
- Databricks
- adagio
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
pygame
pymars
- Ray
starlette
- AIOHTTP
pyspark
- Lightning
raydp
- anyio
tornado
uvicorn
react-router-dom
- accessible-pygments
- alabaster
- cycler
fonttools
jupyterlab-pygments
- soupsieve
- tinycss2
- aim-ui
- alive-progress
bokeh
contourpy
- glfw
halo
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
prompt-toolkit
pyglet
pyopengl
- spinners
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- Rich
- pydot
- alembic
peewee
sqlglot
- adal
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
- gcs-oauth2-boto-plugin
google-auth-oauthlib
- google-oauth
- google-reauth
- id
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
- pyu2f
requests-oauthlib
- cryptography
google-auth-httplib2
- aws-requests-auth
- albucore
- autograd
ax-platform
- bayesian-optimization
- bitsandbytes
botorch
- cma
cmdstanpy
- crcmod
cupy-cuda100
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
- fbgemm-gpu
- gpytorch
gradio-client
- gym
jaxlib
- labmaze
- LangChain
- lightning-utilities
- linear-operator
- llvmlite
lm-eval
- minigrid
- ml-dtypes
- moocore
mosaicml
nltk
- ONNX
onnx-ir
- onnxruntime
onnxscript
openai-whisper
- opt-einsum
optax
- orbax-checkpoint
peft
prophet
pymoo
pyro-ppl
- pytorch-ranger
rouge-score
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
stanio
statsforecast
tf-keras
- tiktoken
timm
tokenizers
- torch-geometric
- torch-optimizer
- torch-scatter
- torch-sparse
torchtext
- triton
- yahp
- gymnasium
jax
- xgboost
lightgbm
- scikit-learn
- MLflow
- datasets
- pytorch-lightning
- comet-ml
- dm-env
flax
- Keras
- torchmetrics
- aim
ale-py
configspace
deepspeed
diffusers
- dm-control
- hpbandster
- hyperopt
- nevergrad
- open-spiel
- Optuna
tensorflow-probability
- zoopt
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
- markdown
markdown-it-py
- mdit-py-plugins
- mdurl
mistune
- moviepy
- nbconvert
- nh3
- openpyxl
- pandocfilters
- pytablewriter
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xlrd
- xmltodict
pillow
- beautifulsoup4
- decord
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-path
- jsonschema-specifications
- openapi-spec-validator
- pathvalidate
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- typepy
- validators
- Pydantic
- jsonschema
- aiobotocore
- applicationinsights
- aws-sam-translator
aws-xray-sdk
- azure-cli-core
- azure-cli-telemetry
- azure-core
- azure-mgmt-compute
- azure-mgmt-core
- azure-mgmt-network
- azure-mgmt-resource
- azure-mgmt-resource-deployments
- boto
- cloud-tpu-diagnostics
- colorlog
- execnet
google-cloud-audit-log
- Gunicorn
- log-symbols
- ml-goodput-measurement
- msrestazure
- opencensus-context
opentelemetry-instrumentation
opentelemetry-instrumentation-asgi
opentelemetry-semantic-conventions
opentelemetry-util-http
- python-json-logger
- supervisor
psutil
- boto3
- botocore
prometheus-client
- pybuildkite
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- ray-haproxy
- typeface-roboto
usehooks-ts
- lowlight
react-window
react-icons
- js-yaml
In common
pyarrow
mcap
- Hugging Face
werkzeug
- React
pydata-sphinx-theme
sphinx-design
- Plotly
- ipywidgets
- torch
- transformers
- TensorFlow
torchvision
markupsafe
myst-parser
- docutils
- jinja2
- MUI
- @mui/icons-material
fiftyone
Refine high-quality datasets and visual AI models
TypeScript11.3kRead on November 12, 2026, at commit 5b951a9What is fiftyone built with?Only in fiftyone
- Vite
- react-relay
- history
- lru-cache
- libsass
- Open3D
accelerate
- pycocotools
- qwen-vl-utils
tensorflow-datasets
umap-learn
- pypandoc
sphinxcontrib-jquery
pydicom
onnxruntime-web
react-error-boundary
notistack
- styled-components
- classnames
@react-spring/web
react-laag
@textea/json-viewer
- Framer
react-syntax-highlighter
rjsf
@monaco-editor/react
re-resizable
- react-input-autosize
- react-plotly.js
react-sortablejs
- material-icons
- react-markdown
remark-gfm
react-color
- react-draggable
three
@lottiefiles/dotlottie-react
@rjsf/core
- react-grid-layout
- react-player
recharts
- html2canvas
@rjsf/utils
- @mui/material
pixi.js
- pixi-viewport
react-three
@sparkjsdev/spark
@xmldom/xmldom
- fast-png
- @mapbox/mapbox-gl-draw
- react-map-gl
- Mapbox
use-resize-observer
- MapLibre
react-mosaic-component
uplot
- xyflow
- hyparquet
- mp4box
- react-virtuoso
allotment
Side by side
Frequently asked questions
Which is bigger, ray or fiftyone?
The proof: ray-project/ray's code at commit de4c576
Which has more GitHub stars, ray or fiftyone?
The proof: ray-project/ray on GitHub
Which has more tests, ray or fiftyone?
The proof: ray-project/ray's code at commit de4c576
Which was updated more recently, ray or fiftyone?
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, ray or fiftyone?
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