diff --git a/vectordb_bench/backend/runner/rate_runner.py b/vectordb_bench/backend/runner/rate_runner.py
index 077c449d4..111597c85 100644
--- a/vectordb_bench/backend/runner/rate_runner.py
+++ b/vectordb_bench/backend/runner/rate_runner.py
@@ -3,6 +3,7 @@
 import multiprocessing as mp
 import time
 from concurrent.futures import ThreadPoolExecutor
+from copy import deepcopy
 
 from vectordb_bench import config
 from vectordb_bench.backend.clients import api
@@ -33,17 +34,23 @@ def __init__(
         self.executing_futures = []
         self.sig_idx = 0
 
-    def send_insert_task(self, db: api.VectorDB, emb: list[list[float]], metadata: list[str], retry_idx: int = 0):
-        _, error = db.insert_embeddings(emb, metadata)
-        if error is not None:
-            log.warning(f"Insert Failed, try_idx={retry_idx}, Exception: {error}")
-            retry_idx += 1
-            if retry_idx <= config.MAX_INSERT_RETRY:
-                time.sleep(retry_idx)
-                self.send_insert_task(db, emb=emb, metadata=metadata, retry_idx=retry_idx)
-            else:
-                msg = f"Insert failed and retried more than {config.MAX_INSERT_RETRY} times"
-                raise RuntimeError(msg) from None
+    def send_insert_task(self, emb: list[list[float]], metadata: list[str]):
+
+        def _insert_embeddings(db: api.VectorDB, emb: list[list[float]], metadata: list[str], retry_idx: int = 0):
+            _, error = db.insert_embeddings(emb, metadata)
+            if error is not None:
+                log.warning(f"Insert Failed, try_idx={retry_idx}, Exception: {error}")
+                retry_idx += 1
+                if retry_idx <= config.MAX_INSERT_RETRY:
+                    time.sleep(retry_idx)
+                    _insert_embeddings(db, emb=emb, metadata=metadata, retry_idx=retry_idx)
+                else:
+                    msg = f"Insert failed and retried more than {config.MAX_INSERT_RETRY} times"
+                    raise RuntimeError(msg) from None
+
+        db_copy = deepcopy(self.db)
+        with db_copy.init():
+            _insert_embeddings(db_copy, emb, metadata, retry_idx=0)
 
     @time_it
     def run_with_rate(self, q: mp.Queue):
@@ -54,7 +61,7 @@ def submit_by_rate() -> bool:
                 rate = self.batch_rate
                 for data in self.dataset:
                     emb, metadata = get_data(data, self.normalize)
-                    self.executing_futures.append(executor.submit(self.send_insert_task, self.db, emb, metadata))
+                    self.executing_futures.append(executor.submit(self.send_insert_task, emb, metadata))
                     rate -= 1
 
                     if rate == 0:
@@ -89,35 +96,35 @@ def check_and_send_signal(wait_interval: float, finished: bool = False):
                     raise e from None
 
             time_per_batch = config.TIME_PER_BATCH
-            with self.db.init():
-                start_time = time.perf_counter()
-                round_idx = 0
 
-                while True:
-                    if len(self.executing_futures) > 200:
-                        log.warning("Skip data insertion this round. There are 200+ unfinished insertion tasks.")
-                    else:
-                        finished, elapsed_time = submit_by_rate()
-                        if finished is True:
-                            log.info(
-                                f"End of dataset, left unfinished={len(self.executing_futures)}, num_round={round_idx}"
-                            )
-                            break
-                        if elapsed_time >= 1.5:
-                            log.warning(
-                                f"Submit insert tasks took {elapsed_time}s, expected 1s, "
-                                f"indicating potential resource limitations on the client machine.",
-                            )
-
-                    check_and_send_signal(wait_interval=0.001, finished=False)
-                    dur = time.perf_counter() - start_time - round_idx * time_per_batch
-                    if dur < time_per_batch:
-                        time.sleep(time_per_batch - dur)
-                    round_idx += 1
-
-                # wait for all tasks in executing_futures to complete
-                while len(self.executing_futures) > 0:
-                    check_and_send_signal(wait_interval=1, finished=True)
-                    round_idx += 1
-
-                log.info(f"Finish all streaming insertion, num_round={round_idx}")
+            start_time = time.perf_counter()
+            round_idx = 0
+
+            while True:
+                if len(self.executing_futures) > 200:
+                    log.warning("Skip data insertion this round. There are 200+ unfinished insertion tasks.")
+                else:
+                    finished, elapsed_time = submit_by_rate()
+                    if finished is True:
+                        log.info(
+                            f"End of dataset, left unfinished={len(self.executing_futures)}, num_round={round_idx}"
+                        )
+                        break
+                    if elapsed_time >= 1.5:
+                        log.warning(
+                            f"Submit insert tasks took {elapsed_time}s, expected 1s, "
+                            f"indicating potential resource limitations on the client machine.",
+                        )
+
+                check_and_send_signal(wait_interval=0.001, finished=False)
+                dur = time.perf_counter() - start_time - round_idx * time_per_batch
+                if dur < time_per_batch:
+                    time.sleep(time_per_batch - dur)
+                round_idx += 1
+
+            # wait for all tasks in executing_futures to complete
+            while len(self.executing_futures) > 0:
+                check_and_send_signal(wait_interval=1, finished=True)
+                round_idx += 1
+
+            log.info(f"Finish all streaming insertion, num_round={round_idx}")