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Update documentation for 0.4.2
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j6k4m8 committed May 7, 2022
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1 change: 1 addition & 0 deletions CHANGELOG.md
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- NEW: `DataFrameBackend` supports operations on a pandas-like API.
- Housekeeping
- Added tests for metadata stores
- Added IGraph and Networkit backends to the standard GitHub Actions CI test suite

## **0.4.1** (February 10, 2022)

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30 changes: 15 additions & 15 deletions README.md
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<th>🔴 = Unsupported</th>
</tr></table>

| Dialect | Description & Notes | Status |
| ------------------ | ---------------------------------------------- | ------ |
| `IGraphDialect` | Python-IGraph interface (no metadata) | 🤔 |
| `NetworkXDialect` | NetworkX-like interface for graph manipulation ||
| `NetworkitDialect` | Networkit-like interface (no metadata) ||

| Backend | Description & Notes | Status |
| ------------------ | ------------------------------------------------- | ------ |
| `DataFrameBackend` | A graph stored in pandas-like tables ||
| `DynamoDBBackend` | Graphs stored in edge/node tables in AWS DynamoDB ||
| `GremlinBackend` | For Gremlin queries (Neptune, Janus, TinkerPop) ||
| `IGraphBackend` | An IGraph graph, in memory ||
| `NetworkitBackend` | A Networkit graph, in memory ||
| `NetworkXBackend` | A NetworkX graph, in memory ||
| `SQLBackend` | A graph stored in two SQL-queryable sister tables ||
| Dialect | Description & Notes | Status |
| ------------------ | ------------------------ | ------ |
| `IGraphDialect` | Python-IGraph interface | |
| `NetworkXDialect` | NetworkX-like interface ||
| `NetworkitDialect` | Networkit-like interface ||

| Backend | Description & Notes | Status |
| ------------------ | ---------------------------- | ------ |
| `DataFrameBackend` | Stored in pandas-like tables ||
| `DynamoDBBackend` | Edge/node tables in DynamoDB ||
| `GremlinBackend` | For Gremlin datastores ||
| `IGraphBackend` | An IGraph graph, in memory ||
| `NetworkitBackend` | A Networkit graph, in memory ||
| `NetworkXBackend` | A NetworkX graph, in memory ||
| `SQLBackend` | Two SQL-queryable tables ||

You can read more about usage and learn about backends and dialects in [the wiki](https://github.com/aplbrain/grand/wiki).

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