Info on compatible connections

dss-plugin-visual-edit/tests/README.md

@@ -1,8 +1,27 @@
-# Integration tests
+# Tests
+
+## Which Connections are compatible with Visual Edit?
+
+As explained in the [deployment guide](https://dataiku.github.io/dss-visual-edit/deploy), we strongly recommend using an SQL connection for the `editlog` and `edits` datasets; it is not necessary to change the connection of the Original Dataset nor of the `edited` dataset.
+
+You may use other connections for demo/evaluation purposes (e.g. looking at the webapp UX and the integration with the Flow).
+
+Here is an overview of what was explicitly tested and what is expected to work.
+
+* **Persisting edits** (i.e. appending rows to the `editlog` dataset):
+  * ✅ We run automated tests on **PostgreSQL** and **FileSystem**.
+  * ✅ We successfully tested manually on **Snowflake**.
+  * ⚠️ We successfully tested manually on **S3** but each edit resulted in a new file, which is not ideal.
+  * ❓ Persisting edits may not work with other connections, including SQL ones. For instance, it fails on BigQuery.
+  * This is because the implementation is based on the `write_dataframe` method of the Dataiku API, which may fail when the dataset is in "append only" mode (as is the case with the `editlog`).
+* **Building `edits` and `edited` datasets** from an `editlog`, and showing edited data in the webapp, is expected to work on all connections as it is based on the `get_dataframe` and `write_dataframe` methods of the Dataiku API.
+* **Initializing a secure `editlog`**: successful manual tests on PostgreSQL (see deployment guide).
+
+## Automated Integration Tests
 
 These tests are written using the Gherkin specification language and a [Dataiku library containing generic Gherkin steps](https://github.com/dataiku/dss-gherkin-steps/blob/main/README.md). See the [parent folder's README](../README.md) for more context.
 
-## Contents
+### Contents
 
 We test the following:
 
@@ -14,7 +33,7 @@ We test the following:
 
 All tests are performed both on a FileSystem and on a PostgreSQL connection. We test that edits are stored in the editlog dataset as expected; we also build the edits and edited datasets and we test their contents as well.
 
-## How to set up an environment to run tests locally
+### How to set up an environment to run tests locally
 
 - Create a Pyhton environment with test requirements found in this directory.
 ```bash