Source: https://seerepo.com/compare/getredash/redash/vs/ray-project/ray
Markdown source: https://seerepo.com/compare/getredash/redash/vs/ray-project/ray.md
Description: redash and ray share 13 technologies: React, Flask, Redis, werkzeug, SQLAlchemy, cryptography, itsdangerous, pyjwt, jinja2, markupsafe, jsonschema, Gunicorn, and Plotly. Both are written in Python.

# redash vs ray

redash and ray share 13 technologies: React, Flask, Redis, werkzeug, SQLAlchemy, cryptography, itsdangerous, pyjwt, jinja2, markupsafe, jsonschema, Gunicorn, and Plotly. Both are written in Python.

- [getredash/redash](https://seerepo.com/r/getredash/redash): Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
- [ray-project/ray](https://seerepo.com/r/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.

## What they share and what sets them apart

- In common: React, Flask, Redis, werkzeug, SQLAlchemy, cryptography, itsdangerous, pyjwt, jinja2, markupsafe, jsonschema, Gunicorn, Plotly
- Only in redash: universal-router, psycopg2-binary, rq, Postgres, ibm-db, oracledb, pyodbc, rq-scheduler, Sentry, flask-restful, history, classnames, antd, react-ace, ace-builds, D3, react-grid-layout, react-resizable, react-virtualized, Ant Design, sqlalchemy-utils, flask-migrate, flask-sqlalchemy, flask-login, authlib, passlib, mustache, xlsxwriter, disposable-email-domains, dompurify, marked, email-validator, wtforms, prop-types, flask-wtf, supervisor, Leaflet, d3-cloud, dnd-kit, leaflet.markercluster, react-plotly.js
- Only in ray: FastAPI, amqp, async-lru, azure-common, azure-datalake-store, azure-storage-blob, confluent-kafka, diskcache, expiringdict, gitdb, google-cloud-core, h5py, kombu, pickleshare, pylance, pymongo, pyarrow, aioboto3, MongoDB, adlfs, smart-open, pyiceberg, pymysql, clickhouse-connect, deltalake, gcsfs, Celery, fastavro, pyzmq, s3fs, webdataset, Google, Hugging Face, Google Cloud Storage, Kafka, asgiref, 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, prompt-toolkit, pyopengl, Textual, widgetsnbextension, xyzservices, Gradio, ipywidgets, matplotlib, Rich, pydot, alembic, peewee, sqlglot, argon2-cffi, argon2-cffi-bindings, azure-identity, flask-basicauth, google-auth-oauthlib, joserfc, jwcrypto, keyring, msal, msal-extensions, oauth2client, oauthlib, requests-oauthlib, google-auth-httplib2, albucore, bitsandbytes, cmdstanpy, crcmod, cupy-cuda12x, cupy-cuda13x, einops, fairscale, gradio-client, gym, LangChain, llvmlite, lm-eval, ml-dtypes, MLflow, nltk, ONNX, onnxruntime, onnxscript, openai-whisper, opt-einsum, orbax-checkpoint, peft, prophet, rouge-score, sacrebleu, safetensors, scikit-image, sentencepiece, skops, tf-keras, tiktoken, timm, tokenizers, torchtext, triton, gymnasium, torch, transformers, TensorFlow, jax, torchvision, xgboost, lightgbm, scikit-learn, accelerate, datasets, pytorch-lightning, evaluate, flax, Keras, 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, markdown-it-py, mdurl, mistune, moviepy, nbconvert, nh3, openpyxl, pandocfilters, ruamel-yaml, webencodings, xlrd, xmltodict, pillow, docutils, beautifulsoup4, av, nbformat, torchcodec, annotated-types, fastjsonschema, fqdn, jsonschema-specifications, pathvalidate, pydantic-core, referencing, rfc3339-validator, rfc3986, rfc3986-validator, validators, Pydantic, openapi-schema-validator, aiobotocore, azure-mgmt-compute, azure-mgmt-resource, colorlog, 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

## Side by side

| | redash | ray |
|---|---|---|
| Size | 120,621 lines written, 643 code files | 1,531,664 lines written, 2,777 code files |
| Who writes it | 0.9% of its commits signed by AI. With Claude Code and Cursor | 3.6% of its commits signed by AI. With Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex |
| Activity | Last push November 7, 2026, 6,566 commits, 28,874 stars | Last push November 6, 2026, 32,373 commits, 44,213 stars |
| Tests | 266 test files. 21.6% of its code files have a test that imports them | 2,168 test files. 9.7% of its code files have a test that imports them |

- Size: Lines written by people and agents, without generated ones; code files, without tests.
- Who writes it: A commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
- Activity: From GitHub and its history, on the day SeeRepo read it.
- Tests: The files that test the code, and the share of code files a test imports.

## Frequently asked questions

### Which is bigger, redash or ray?

ray, with 1,531,664 lines written; redash has 120,621.

The proof: [ray-project/ray's code at commit 77567c5](https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)

### Which has more GitHub stars, redash or ray?

ray, with 44,213 stars; redash has 28,874.

The proof: [ray-project/ray on GitHub](https://github.com/ray-project/ray)

### Which has more tests, redash or ray?

ray, with 2,168 test files; redash has 266.

The proof: [ray-project/ray's code at commit 77567c5](https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)

### Which was updated more recently, redash or ray?

redash: its last push was on November 7, 2026, and ray's on November 6, 2026.

The proof: [getredash/redash's commits on GitHub](https://github.com/getredash/redash/commits)

### Which has more commits signed by AI, redash or ray?

ray: an AI signed 3.6% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex; in redash, 0.9%.

The proof: [the commits each tool signed in ray-project/ray](https://seerepo.com/r/ray-project/ray/ai)

## Sources

- getredash/redash: Read on November 8, 2026, at commit 09740ea (https://github.com/getredash/redash/tree/09740eaf6359af4ac4f932b620f28add2299142e)
- ray-project/ray: Read on November 6, 2026, at commit 77567c5 (https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)

## What is your repo built with?

Any public repo, with no account: https://seerepo.com/r/owner/repo/built, with the owner and name it has on GitHub.