blacksmithgu/datacore
blacksmithgu/datacore has 2,247 GitHub stars and 70 forks. GitHot measured 0 stars in 24 hours and +2 in 7 days. Last checked 2026-11-05 08:18 UTC. Last push 2026-06-22.
Work-in-progress successor to Dataview with a focus on UX and speed.
Measured star growth
- in 24h
- 0
- in 7 days
- +2
- in 15 days
- Collecting history
- in 1 month
- Collecting history
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
README.md
OriginalDatacore
Datacore is a work-in-progress re-imagining of Dataview with a focus on 2-10x better query and rendering performance, as well as fully interactable views.
Documentation
You can find the current documentation at https://blacksmithgu.github.io/datacore/.
Roadmap
Datacore is a work in progress. For more details, check out the roadmap.
Differences from Dataview
Datacore is fundamentally the same thing as dataview - an index over Markdown files that supports live-updating views and metadata. However, Datacore focuses on substantial index changes for performance, as well as a new sleek UI which completely replaces traditional Dataview queries. Datacore supports all query operations that Dataview does, with some extra functionality.
- New Javascript API: Javascript-based views are now React-based and support internal state, flickerless updates on
index changes, and a new query API which is much more performant than
dv.pages().where(...). - WYSIWYG Views: Datacore queries now use a responsive table view and can be manipulated with a table editor much more akin to what you would see in places like Notion and Airtable.
- Functioning Embeds: Markdown page, image, and video embeds now work in all views, and a new special view type which is just a list of embeds has been added.
- Live Editing: Values inside of table views can now be edited; task views include more nuanced rendering of metadata like due date and more operations for manipulating tasks directly.
- Section / Block Queries: Datacore indexes all files (including attachments, PDFs, and images), and supports queries at section and block level granularity.
Compiling & Building
You can do a first-time setup of the repository by making sure you have yarn installed and then just running
yarn install
yarn run build
This will invoke esbuild under the hood and dump the final plugin into the /build directory. There is a short script which can then copy the compiled plugin into your vault -
./scripts/install-built /path/to/your/vault/root
You can combine the build and install into a single command:
yarn run build && ./scripts/install-built /path/to/your/vault/root
Formatting & Running Tests
You can format your code via
yarn run format
And you can run jest tests via
yarn run test
Contributing
Discord: https://discord.gg/KwZUX4BYba.
Contributions are welcome; for any contributions beyond bug fixes, we recommend reaching out via email or discord to make sure what you are trying to implement is reasonable / feasible!
Explore related projects
Asabeneh/30-Days-Of-Python
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,163 starsgrafana/grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
77,699 starsredis/redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
77,199 starsapache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
75,413 stars