hydra vs ray
hydra and ray share 8 technologies: AIOHTTP, Ray, ax-platform, torch, nevergrad, Optuna, colorlog, and boto3. Both are written in Python.
What they share and what sets them apart
hydra-ecosystem
hydra
Hydra is a framework for elegantly configuring complex applications
Python10.7kRead on November 13, 2026, at commit fdd1cbbWhat is hydra built with?Only in hydra
rq
- submitit
In common
ray-project
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
pyarrow
mcap
- 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
- Hugging Face
- Google Cloud Storage
- Kafka
- Databricks
- adagio
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
pygame
pymars
werkzeug
starlette
pyspark
- Lightning
raydp
- anyio
tornado
uvicorn
- React
react-router-dom
- accessible-pygments
- alabaster
- cycler
fonttools
jupyterlab-pygments
pydata-sphinx-theme
- soupsieve
sphinx-design
- tinycss2
- aim-ui
- alive-progress
bokeh
contourpy
- glfw
halo
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyglet
pyopengl
- spinners
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
- 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
- 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
- transformers
- TensorFlow
jax
torchvision
- 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
- open-spiel
tensorflow-probability
- zoopt
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
- markdown
markdown-it-py
markupsafe
- mdit-py-plugins
- mdurl
mistune
- moviepy
myst-parser
- nbconvert
- nh3
- openpyxl
- pandocfilters
- pytablewriter
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xlrd
- xmltodict
pillow
- docutils
- jinja2
- 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
- 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
- botocore
prometheus-client
- pybuildkite
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- ray-haproxy
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
Side by side
hydraray
SizeLines written by people and agents, without generated ones; code files, without tests.
hydra71,178 lines written121 code files
ray1,566,356 lines written2,810 code files
Who writes itA commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
hydra0.4% of its commits signed by AIWith GitHub Copilot, Claude Code, and Cursor
ray3.7% of its commits signed by AIWith Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex
ActivityFrom GitHub and its history, on the day SeeRepo read it.
hydraLast push November 12, 20262,248 commits10,744 stars
rayLast push November 13, 202632,468 commits44,282 stars
TestsThe files that test the code, and the share of code files a test imports.
hydra250 test files60.3% of its code files have a test that imports them
ray2,208 test files9.4% of its code files have a test that imports them
Frequently asked questions
Which is bigger, hydra or ray?
ray, with 1,566,356 lines written; hydra has 71,178.
The proof: ray-project/ray's code at commit de4c576
Which has more GitHub stars, hydra or ray?
ray, with 44,282 stars; hydra has 10,744.
The proof: ray-project/ray on GitHub
Which has more tests, hydra or ray?
ray, with 2,208 test files; hydra has 250.
The proof: ray-project/ray's code at commit de4c576
Which was updated more recently, hydra or ray?
ray: its last push was on November 13, 2026, and hydra's on November 12, 2026.
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, hydra or ray?
ray: an AI signed 3.7% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex; in hydra, 0.4%.
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