diff --git a/docs/graph/athena.rst b/docs/graph/athena.rst
--- a/docs/graph/athena.rst
+++ b/docs/graph/athena.rst
@@ -39,28 +39,21 @@
 Athena needs to be made aware of the location and the schema of the Parquet
 files available as a public dataset. Unfortunately, since Athena does not
 support queries that contain multiple commands, it is not as simple as pasting
-an installation script in the console. Instead, we provide a Python script that
-can be run locally on your machine, that will communicate with Athena to create
+an installation script in the console. Instead, you can use the ``swh dataset
+athena`` command on your local machine, which will query Athena to create
 the tables automatically with the appropriate schema.
 
-To run this script, you will need to install a few dependencies on your
-machine:
+First, install the ``swh.dataset`` Python module from PyPI::
 
-- For **Ubuntu** and **Debian**::
-
-    sudo apt install python3 python3-boto3 awscli
-
-- For **Archlinux**::
-
-    sudo pacman -S --needed python python-boto3 aws-cli
+    pip install swh.dataset
 
 Once the dependencies are installed, run::
 
-  aws configure
+    aws configure
 
 This will ask for an AWS Access Key ID and an AWS Secret Access Key in
-order to give Python access to your AWS account. These keys can be generated at
-`this address
+order to give the Boto3 library access to your AWS account. These keys can be
+generated at `this address
 <https://console.aws.amazon.com/iam/home#/security_credentials>`_.
 
 It will also ask for the region in which you want to run the queries. We
@@ -70,30 +63,14 @@
 Creating the tables
 ~~~~~~~~~~~~~~~~~~~
 
-Download and run the Python script that will create the tables on your account:
-
-.. tabs::
-
-  .. group-tab:: full
-
-    ::
-
-      wget https://annex.softwareheritage.org/public/dataset/graph/latest/athena/athena.py
-      python3 athena.py -o 's3://YOUR_OUTPUT_BUCKET/'
+The ``swh dataset athena create`` command can be used to create the tables on
+your Athena instance. For example, to create the tables of the 2021-03-23
+graph::
 
-  .. group-tab:: teaser: popular-4k
-
-    ::
-
-      wget https://annex.softwareheritage.org/public/dataset/graph/latest/athena/athena.py
-      python3 athena.py -o 's3://YOUR_OUTPUT_BUCKET/' -d popular4k -l 's3://softwareheritage/teasers/popular-4k'
-
-  .. group-tab:: teaser: popular-3k-python
-
-    ::
-
-      wget https://annex.softwareheritage.org/public/dataset/graph/latest/athena/athena.py
-      python3 athena.py -o 's3://YOUR_OUTPUT_BUCKET/' -d popular3kpython -l 's3://softwareheritage/teasers/popular-3k-python'
+    swh dataset athena create \
+        --database-name swh_graph_2021_03_23
+        --location-prefix s3://softwareheritage/graph/2021-03-23/orc
+        --output-location s3://YOUR_OUTPUT_BUCKET/
 
 To check that the tables have been successfully created in your account, you
 can open your `Amazon Athena console
@@ -115,7 +92,7 @@
 archive::
 
   SELECT from_utf8(name, '?') AS name, COUNT(DISTINCT target) AS cnt
-  FROM directory_entry_file
+  FROM directory_entry
   GROUP BY name
   ORDER BY cnt DESC
   LIMIT 10;
@@ -123,3 +100,11 @@
 Other examples are available in the preprint of our article: `The Software
 Heritage Graph Dataset: Public software development under one roof.
 <https://upsilon.cc/~zack/research/publications/msr-2019-swh.pdf>`_
+
+It is also possible to query Athena directly from the command line, using the
+``swh dataset athena query`` command::
+
+    echo "select message from revision limit 10;" |
+    swh dataset athena query \
+        --database-name swh_graph_2021_03_23
+        --output-location s3://YOUR_OUTPUT_BUCKET/
diff --git a/docs/graph/databricks.rst b/docs/graph/databricks.rst
--- a/docs/graph/databricks.rst
+++ b/docs/graph/databricks.rst
@@ -37,7 +37,6 @@
 
     [FileInfo(path='abfss://.../swh/content/', name='content/', size=0),
      FileInfo(path='abfss://.../swh/directory/', name='directory/', size=0),
-     FileInfo(path='abfss://.../swh/directory_entry_dir/', name='directory_entry_dir/', size=0),
      ...]
 
 Loading the tables
@@ -55,19 +54,16 @@
     tables = [
       'content',
       'directory',
-      'directory_entry_dir',
-      'directory_entry_file',
-      'directory_entry_rev',
+      'directory_entry',
       'origin',
       'origin_visit',
-      'person',
+      'origin_visit_status',
       'release',
       'revision',
       'revision_history',
       'skipped_content',
       'snapshot',
       'snapshot_branch',
-      'snapshot_branches'
     ]
 
     for table in tables:
diff --git a/docs/graph/schema.rst b/docs/graph/schema.rst
--- a/docs/graph/schema.rst
+++ b/docs/graph/schema.rst
@@ -3,12 +3,14 @@
 
 The Merkle DAG of the Software Heritage archive is encoded in the dataset as a
 set of relational tables.
+
+This page documents the relational schema of the **latest version** of the
+graph dataset.
+
 A simplified view of the corresponding database schema is shown here:
 
 .. image:: _images/dataset-schema.svg
 
-This page documents the details of the schema.
-
 **Note**: To limit abuse, some columns containing personal information are
 pseudonimized in the dataset using a hash algorithm. Individual authors may be
 retrieved by querying the Software Heritage API.