diff --git a/pyrit/memory/sqlite_memory.py b/pyrit/memory/sqlite_memory.py
index da28bc01b..9dd3561f4 100644
--- a/pyrit/memory/sqlite_memory.py
+++ b/pyrit/memory/sqlite_memory.py
@@ -8,7 +8,7 @@
 from contextlib import closing, suppress
 from datetime import datetime
 from pathlib import Path
-from typing import Any, Optional, TypeVar, Union
+from typing import Any, Optional, TypeVar, Union, cast
 
 from sqlalchemy import and_, create_engine, func, or_, text
 from sqlalchemy.engine.base import Engine
@@ -35,6 +35,14 @@
 Model = TypeVar("Model")
 
 
+class _ExportableConversationPiece:
+    def __init__(self, data: dict[str, Any]) -> None:
+        self._data = data
+
+    def to_dict(self) -> dict[str, Any]:
+        return self._data
+
+
 class SQLiteMemory(MemoryInterface, metaclass=Singleton):
     """
     A memory interface that uses SQLite as the backend database.
@@ -474,6 +482,9 @@ def export_conversations(
 
         Returns:
             Path: The path to the exported file.
+
+        Raises:
+            ValueError: If the specified export format is not supported.
         """
         # Import here to avoid circular import issues
         from pyrit.memory.memory_exporter import MemoryExporter
@@ -522,9 +533,20 @@ def export_conversations(
             piece_data["scores"] = [score.to_dict() for score in piece_scores]
             merged_data.append(piece_data)
 
-        # Export to JSON manually since the exporter expects objects but we have dicts
-        with open(file_path, "w") as f:
-            json.dump(merged_data, f, indent=4)
+        if not merged_data:
+            if export_type == "json":
+                with open(file_path, "w", encoding="utf-8") as f:
+                    json.dump(merged_data, f, indent=4)
+            elif export_type in self.exporter.export_strategies:
+                file_path.write_text("", encoding="utf-8")
+            else:
+                raise ValueError(f"Unsupported export format: {export_type}")
+            return file_path
+
+        exportable_pieces = [_ExportableConversationPiece(data=piece_data) for piece_data in merged_data]
+        self.exporter.export_data(
+            cast("list[MessagePiece]", exportable_pieces), file_path=file_path, export_type=export_type
+        )
         return file_path
 
     def print_schema(self) -> None:
diff --git a/tests/unit/memory/memory_interface/test_interface_export.py b/tests/unit/memory/memory_interface/test_interface_export.py
index 14064b718..42d4e6d80 100644
--- a/tests/unit/memory/memory_interface/test_interface_export.py
+++ b/tests/unit/memory/memory_interface/test_interface_export.py
@@ -1,12 +1,16 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT license.
 
+import csv
+import json
 import os
 import tempfile
 from collections.abc import Sequence
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 
+import pytest
+
 from pyrit.common.path import DB_DATA_PATH
 from pyrit.memory import MemoryExporter, MemoryInterface
 from pyrit.models import MessagePiece
@@ -103,8 +107,6 @@ def test_export_all_conversations_with_scores_correct_data(sqlite_instance: Memo
             assert file_path.exists()
 
             # Read and verify the exported JSON content
-            import json
-
             with open(file_path) as f:
                 exported_data = json.load(f)
 
@@ -141,8 +143,6 @@ def test_export_all_conversations_with_scores_empty_data(sqlite_instance: Memory
             assert file_path.exists()
 
             # Read and verify the exported JSON content is empty
-            import json
-
             with open(file_path) as f:
                 exported_data = json.load(f)
 
@@ -151,3 +151,57 @@ def test_export_all_conversations_with_scores_empty_data(sqlite_instance: Memory
         # Clean up the temp file
         if file_path.exists():
             os.remove(file_path)
+
+
+@pytest.mark.parametrize("export_type, suffix", [("json", ".json"), ("csv", ".csv"), ("md", ".md")])
+def test_export_all_conversations_with_scores_respects_export_type(
+    sqlite_instance: MemoryInterface, export_type: str, suffix: str
+):
+    sqlite_instance.exporter = MemoryExporter()
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
+        file_path = Path(temp_file.name)
+        temp_file.close()
+
+    try:
+        with (
+            patch.object(sqlite_instance, "get_message_pieces") as mock_get_pieces,
+            patch.object(sqlite_instance, "get_prompt_scores") as mock_get_scores,
+        ):
+            mock_piece = MagicMock()
+            mock_piece.id = "piece_id_1234"
+            mock_piece.to_dict.return_value = {
+                "id": "piece_id_1234",
+                "converted_value": "sample piece",
+            }
+
+            mock_score = MagicMock()
+            mock_score.message_piece_id = "piece_id_1234"
+            mock_score.to_dict.return_value = {"message_piece_id": "piece_id_1234", "score_value": 10}
+
+            mock_get_pieces.return_value = [mock_piece]
+            mock_get_scores.return_value = [mock_score]
+
+            sqlite_instance.export_conversations(file_path=file_path, export_type=export_type)
+
+            assert file_path.exists()
+            exported_content = file_path.read_text(encoding="utf-8")
+            assert "piece_id_1234" in exported_content
+            assert "sample piece" in exported_content
+
+            if export_type == "json":
+                exported_data = json.loads(exported_content)
+                assert len(exported_data) == 1
+                assert exported_data[0]["id"] == "piece_id_1234"
+            elif export_type == "csv":
+                with open(file_path, newline="") as exported_file:
+                    reader = csv.DictReader(exported_file)
+                    assert reader.fieldnames == ["id", "converted_value", "scores"]
+                    rows = list(reader)
+                assert len(rows) == 1
+                assert rows[0]["id"] == "piece_id_1234"
+            elif export_type == "md":
+                assert exported_content.startswith("| id | converted_value | scores |")
+    finally:
+        if file_path.exists():
+            os.remove(file_path)