{"id":27200578,"url":"https://github.com/dreden33773/embergraph","last_synced_at":"2026-05-09T15:21:36.973Z","repository":{"id":283747073,"uuid":"952771991","full_name":"DrEden33773/EmberGraph","owner":"DrEden33773","description":"To query a `multi directed graph` with `label + attribute filtering` efficiently, support Neo4j and SQLite3 as storage layer.","archived":false,"fork":false,"pushed_at":"2025-04-08T16:55:29.000Z","size":475,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-08T17:38:49.841Z","etag":null,"topics":["graduation-project","graph-database","neo4j","parallel-computing","polars","python3","rust","sqlite3","subgraph-matching","tokio"],"latest_commit_sha":null,"homepage":"","language":"Rust","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DrEden33773.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-21T21:18:20.000Z","updated_at":"2025-04-08T17:16:24.000Z","dependencies_parsed_at":null,"dependency_job_id":"133ca3c0-20b4-4fb3-a1a2-61d48edf691e","html_url":"https://github.com/DrEden33773/EmberGraph","commit_stats":null,"previous_names":["dreden33773/ember-sgm-backend","dreden33773/embergraph"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DrEden33773%2FEmberGraph","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DrEden33773%2FEmberGraph/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DrEden33773%2FEmberGraph/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DrEden33773%2FEmberGraph/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DrEden33773","download_url":"https://codeload.github.com/DrEden33773/EmberGraph/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248114353,"owners_count":21050017,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["graduation-project","graph-database","neo4j","parallel-computing","polars","python3","rust","sqlite3","subgraph-matching","tokio"],"created_at":"2025-04-09T21:29:32.864Z","updated_at":"2026-05-09T15:21:36.951Z","avatar_url":"https://github.com/DrEden33773.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# EmberGraph (pre-published)\n\nTo query a pattern on `multi directed graph` with `label / attribute filtering` efficiently, support `Neo4j` and `SQLite3` as the storage layer.\n\n\u003e ## ❤️ Please give a `Star` / `Follow` if you like this project\n\n## To begin with\n\nThe project is still under development, however it has already been proved to be a correct implementation.\n\nThe test dataset is `LDBC-SNB-SF0.1`, and the example used for testing all come from `LDBC-SNB Business Intelligence (BI 1 ~ 20)`. You could find the actual `query` statements from `./resources/cypher`.\n\n`EmberGraph` is only one-more-step to be formally published:\n\n\u003e To **optimize** the `matching order generation algorithm` (most likely to be `iterative dynamic programming` just like what `Neo4j` has done since it's `2.2` version)\n\n## What's the most impressive?\n\nEven though we're still working on the one-last-step to use the **better** `matching-order seeking strategy`, the performance of this `pre-published version` is approximately **equivalent** to that of `Neo4j`. (Oh, even **faster** in some cases!)\n\n## How to build\n\nYou should have installed `git-lfs` first, to correctly clone this project:\n\n```bash\ngit clone https://github.com/DrEden33773/EmberGraph\ngit lfs pull\ncargo build # This will automatically install uv if in need, and then initialize `./ember-graph-import`\n```\n\nThen, you should manually do some initialization steps:\n\n1. Transformed the original dataset into a `Neo4j-import-friendly` one. (Using `./ember-graph-import/raw_data_formatter.py`)\n2. Generated basic `label-based` statistics. (Using `./ember-graph-import/statistics_generator.py`)\n3. Imported `Neo4j-import-friendly` dataset into `Neo4j` or `SQLite3`. (Using `./ember-graph-import/neo4j_admin_import.py` or `./ember-graph-import/sqlite_import.py`)\n\nAll of the `python scripts` mentioned above could executed via the command:\n\n```bash\ncd ./ember-graph-import\nsource ./.venv/bin/activate\nuv run \u003cSCRIPT-NAME\u003e\n```\n\nRight now, if you want to, you could run commands:\n\n```bash\ncargo run --example bi_\u003cx\u003e # (where x in [1..=20])\n```\n\nTo check the query result of `bi_1` to `bi_20`.\n\n## Something important for `release` mode building\n\nYes, you might have guessed -- It's totally possible to get the highest performance to build under the `release` mode.\n\nHowever, I have to mind you that could be `TOO SLOW`.\n\nSo, if you really don't mind, here're several better options:\n\n- Linux:\n  \n```bash\ncargo build --release --all-target -j $(nproc)\n```\n\n- Mac:\n\n```bash\ncargo build --release --all-target -j $(sysctl -n hw.ncpu)\n```\n\n- Windows(Powershell):\n\n```powershell\ncargo build --release --all-target -j $env:NUMBER_OF_PROCESSORS\n```\n\n- Windows(CMD):\n\n```cmd\ncargo build --release --all-target -j %NUMBER_OF_PROCESSORS%\n```\n\nAfter all, that's a short-term pain for long-term gain😂.\n\nThen, you could run the command below to check the query result of `bi_1` to `bi_20`:\n\n```bash\ncargo run --release --example bi_\u003cx\u003e # (where x in [1..=20])\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdreden33773%2Fembergraph","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdreden33773%2Fembergraph","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdreden33773%2Fembergraph/lists"}