diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py
index 118d70d78..785773b39 100644
--- a/freqtrade/rpc/api_server/api_ws.py
+++ b/freqtrade/rpc/api_server/api_ws.py
@@ -84,11 +84,8 @@ async def _process_consumer_request(
             # Limit the amount of candles per dataframe to 'limit' or 1500
             limit = max(data.get('limit', 1500), 1500)
 
-        # They requested the full historical analyzed dataframes
-        analyzed_df = rpc._ws_request_analyzed_df(limit)
-
-        # For every dataframe, send as a separate message
-        for _, message in analyzed_df.items():
+        # For every pair in the generator, send a separate message
+        for message in rpc._ws_request_analyzed_df(limit):
             response = WSAnalyzedDFMessage(data=message)
             await channel_manager.send_direct(channel, response.dict(exclude_none=True))
 
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 143b11911..55bb5a34b 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -5,7 +5,7 @@ import logging
 from abc import abstractmethod
 from datetime import date, datetime, timedelta, timezone
 from math import isnan
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Dict, Generator, List, Optional, Tuple, Union
 
 import arrow
 import psutil
@@ -1063,23 +1063,20 @@ class RPC:
         self,
         pairlist: List[str],
         limit: Optional[int]
-    ) -> Dict[str, Any]:
+    ) -> Generator[Dict[str, Any], None, None]:
         """ Get the analysed dataframes of each pair in the pairlist """
         timeframe = self._freqtrade.config['timeframe']
         candle_type = self._freqtrade.config.get('candle_type_def', CandleType.SPOT)
-        _data = {}
 
         for pair in pairlist:
             dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit)
 
-            _data[pair] = {
+            yield {
                 "key": (pair, timeframe, candle_type),
                 "df": dataframe,
                 "la": last_analyzed
             }
 
-        return _data
-
     def _ws_request_analyzed_df(self, limit: Optional[int]):
         """ Historical Analyzed Dataframes for WebSocket """
         whitelist = self._freqtrade.active_pair_whitelist