diff --git a/oravector-demo/sql/setup_vector_schema.sql b/oravector-demo/sql/setup_vector_schema.sql
new file mode 100644
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+++ b/oravector-demo/sql/setup_vector_schema.sql
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+-- Oracle 26ai setup for the in-database embedding backend (port 8002)
+-- Run as SYSDBA connected to FREEPDB1
+--
+-- Prerequisites:
+--   - CLIP_TXT and CLIP_IMG ONNX model files must be present in the Oracle
+--     VEC_DUMP directory before loading (see notes below)
+--   - vector_memory_size must be set in SGA (512M recommended)
+--
+-- Usage:
+--   podman exec -it oracle.free sqlplus / as sysdba
+
+ALTER SESSION SET CONTAINER=FREEPDB1;
+
+-- Create VECTOR user
+CREATE USER vector IDENTIFIED BY Vektor;
+GRANT CONNECT, RESOURCE TO vector;
+GRANT UNLIMITED TABLESPACE TO vector;
+GRANT READ, WRITE ON DIRECTORY VEC_DUMP TO vector;
+
+-- Load ONNX models (run as VECTOR user or SYSDBA)
+-- The .onnx files must be placed in the VEC_DUMP directory on the Oracle host
+-- beforehand (typically /opt/oracle/dbs/vec_dump/ inside the container).
+--
+-- CLIP_TXT: text encoder using CLS-token pooling (position 0).
+-- Standard CLIP exports use EOS-token pooling (ArgMax), which Oracle rejects
+-- because it introduces an ArgMax node on input_ids. This model must be
+-- re-exported with CLS pooling to pass Oracle's ONNX validator.
+--
+EXEC DBMS_VECTOR.LOAD_ONNX_MODEL('VEC_DUMP', 'clip_txt.onnx', 'CLIP_TXT',
+    JSON('{"function":"embedding","embeddingOutput":"output","input":{"input":["DATA"]}}'));
+
+EXEC DBMS_VECTOR.LOAD_ONNX_MODEL('VEC_DUMP', 'clip_img.onnx', 'CLIP_IMG',
+    JSON('{"function":"embedding","embeddingOutput":"output","input":{"input":["DATA"]}}'));
+
+-- Photo table (stores filename, image BLOB, and vector)
+CREATE TABLE vector.foto_vektor (
+    id        NUMBER GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
+    filename  VARCHAR2(100),
+    foto      BLOB,
+    foto_vek  VECTOR
+);
+
+-- Grant SELECT on FOTO_VEKTOR to vectors_user so both backends share one table
+-- (optional — remove if the schemas should remain isolated)
+GRANT SELECT ON vector.foto_vektor TO vectors_user;
+
+EXIT;
diff --git a/oravector-demo/sql/setup_vectors_user.sql b/oravector-demo/sql/setup_vectors_user.sql
new file mode 100644
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+++ b/oravector-demo/sql/setup_vectors_user.sql
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+-- Oracle 26ai setup for the Python-embedding backend (port 8001)
+-- Run as SYSDBA connected to FREEPDB1
+--
+-- Usage (from host):
+--   podman exec oracle.free bash -c "sqlplus -s / as sysdba @/tmp/setup_vectors_user.sql"
+--
+-- Or interactively:
+--   podman exec -it oracle.free sqlplus / as sysdba
+--   ALTER SESSION SET CONTAINER=FREEPDB1;
+--   @setup_vectors_user.sql
+
+ALTER SESSION SET CONTAINER=FREEPDB1;
+
+-- Create user
+CREATE USER vectors_user IDENTIFIED BY Vektor;
+GRANT CONNECT, RESOURCE TO vectors_user;
+GRANT UNLIMITED TABLESPACE TO vectors_user;
+
+-- Switch to vectors_user and create schema objects
+-- (run the following block connected as vectors_user)
+
+-- Table
+CREATE TABLE vectors_user.images (
+    id        NUMBER GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
+    filename  VARCHAR2(255) NOT NULL UNIQUE,
+    filepath  VARCHAR2(1000) NOT NULL,
+    embedding VECTOR(512, FLOAT32)
+);
+
+-- HNSW vector index (requires vector_memory_size > 0 in SGA)
+CREATE VECTOR INDEX vectors_user.images_embedding_idx
+    ON vectors_user.images(embedding)
+    ORGANIZATION INMEMORY NEIGHBOR GRAPH
+    WITH DISTANCE COSINE
+    WITH TARGET ACCURACY 95
+    PARAMETERS (type HNSW, neighbors 32, efconstruction 200);
+
+EXIT;
diff --git a/pgvector-demo/sql/setup.sql b/pgvector-demo/sql/setup.sql
new file mode 100644
index 0000000..edff597
--- /dev/null
+++ b/pgvector-demo/sql/setup.sql
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+-- PostgreSQL setup for pgvector demo
+-- Run as superuser (dl) against the vectors_demo database
+--
+-- Usage:
+--   docker exec -i postgresql-database-1 psql -U dl -d vectors_demo -f - < pgvector-demo/sql/setup.sql
+
+CREATE EXTENSION IF NOT EXISTS vector;
+
+CREATE TABLE IF NOT EXISTS images (
+    id        SERIAL PRIMARY KEY,
+    filename  TEXT NOT NULL UNIQUE,
+    filepath  TEXT NOT NULL,
+    embedding vector(512)
+);
+
+CREATE INDEX IF NOT EXISTS images_embedding_idx
+    ON images USING hnsw (embedding vector_cosine_ops);