diff --git a/vectordb_bench/backend/clients/api.py b/vectordb_bench/backend/clients/api.py
index ce2b05650..8070164dd 100644
--- a/vectordb_bench/backend/clients/api.py
+++ b/vectordb_bench/backend/clients/api.py
@@ -16,10 +16,14 @@ class MetricType(str, Enum):
 
 class IndexType(str, Enum):
     HNSW = "HNSW"
+    HNSW_SQ = "HNSW_SQ"
+    HNSW_PQ = "HNSW_PQ"
+    HNSW_PRQ = "HNSW_PRQ"
     DISKANN = "DISKANN"
     STREAMING_DISKANN = "DISKANN"
     IVFFlat = "IVF_FLAT"
     IVFSQ8 = "IVF_SQ8"
+    IVF_RABITQ = "IVF_RABITQ"
     Flat = "FLAT"
     AUTOINDEX = "AUTOINDEX"
     ES_HNSW = "hnsw"
@@ -31,6 +35,14 @@ class IndexType(str, Enum):
     SCANN = "scann"
 
 
+class SQType(str, Enum):
+    SQ6 = "SQ6"
+    SQ8 = "SQ8"
+    BF16 = "BF16"
+    FP16 = "FP16"
+    FP32 = "FP32"
+
+
 class DBConfig(ABC, BaseModel):
     """DBConfig contains the connection info of vector database
 
diff --git a/vectordb_bench/backend/clients/milvus/config.py b/vectordb_bench/backend/clients/milvus/config.py
index e3a3f9b19..07cd9aad8 100644
--- a/vectordb_bench/backend/clients/milvus/config.py
+++ b/vectordb_bench/backend/clients/milvus/config.py
@@ -1,6 +1,6 @@
 from pydantic import BaseModel, SecretStr, validator
 
-from ..api import DBCaseConfig, DBConfig, IndexType, MetricType
+from ..api import DBCaseConfig, DBConfig, IndexType, MetricType, SQType
 
 
 class MilvusConfig(DBConfig):
@@ -88,6 +88,88 @@ def search_param(self) -> dict:
         }
 
 
+class HNSWSQConfig(HNSWConfig, DBCaseConfig):
+    index: IndexType = IndexType.HNSW_SQ
+    sq_type: SQType = SQType.SQ8
+    refine: bool = True
+    refine_type: SQType = SQType.FP32
+    refine_k: float = 1
+
+    def index_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "index_type": self.index.value,
+            "params": {
+                "M": self.M,
+                "efConstruction": self.efConstruction,
+                "sq_type": self.sq_type.value,
+                "refine": self.refine,
+                "refine_type": self.refine_type.value,
+            },
+        }
+
+    def search_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "params": {"ef": self.ef, "refine_k": self.refine_k},
+        }
+
+
+class HNSWPQConfig(HNSWConfig):
+    index: IndexType = IndexType.HNSW_PQ
+    m: int = 32
+    nbits: int = 8
+    refine: bool = True
+    refine_type: SQType = SQType.FP32
+    refine_k: float = 1
+
+    def index_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "index_type": self.index.value,
+            "params": {
+                "M": self.M,
+                "efConstruction": self.efConstruction,
+                "m": self.m,
+                "nbits": self.nbits,
+                "refine": self.refine,
+                "refine_type": self.refine_type.value,
+            },
+        }
+
+    def search_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "params": {"ef": self.ef, "refine_k": self.refine_k},
+        }
+
+
+class HNSWPRQConfig(HNSWPQConfig):
+    index: IndexType = IndexType.HNSW_PRQ
+    nrq: int = 2
+
+    def index_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "index_type": self.index.value,
+            "params": {
+                "M": self.M,
+                "efConstruction": self.efConstruction,
+                "m": self.m,
+                "nbits": self.nbits,
+                "nrq": self.nrq,
+                "refine": self.refine,
+                "refine_type": self.refine_type.value,
+            },
+        }
+
+    def search_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "params": {"ef": self.ef, "refine_k": self.refine_k},
+        }
+
+
 class DISKANNConfig(MilvusIndexConfig, DBCaseConfig):
     search_list: int | None = None
     index: IndexType = IndexType.DISKANN
@@ -144,6 +226,31 @@ def search_param(self) -> dict:
         }
 
 
+class IVFRABITQConfig(IVFSQ8Config):
+    index: IndexType = IndexType.IVF_RABITQ
+    rbq_bits_query: int = 0  # 0, 1, 2, ..., 8
+    refine: bool = True
+    refine_type: SQType = SQType.FP32
+    refine_k: float = 1
+
+    def index_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "index_type": self.index.value,
+            "params": {
+                "nlist": self.nlist,
+                "refine": self.refine,
+                "refine_type": self.refine_type.value,
+            },
+        }
+
+    def search_param(self) -> dict:
+        return {
+            "metric_type": self.parse_metric(),
+            "params": {"nprobe": self.nprobe, "rbq_bits_query": self.rbq_bits_query, "refine_k": self.refine_k},
+        }
+
+
 class FLATConfig(MilvusIndexConfig, DBCaseConfig):
     index: IndexType = IndexType.Flat
 
@@ -285,9 +392,13 @@ def search_param(self) -> dict:
 _milvus_case_config = {
     IndexType.AUTOINDEX: AutoIndexConfig,
     IndexType.HNSW: HNSWConfig,
+    IndexType.HNSW_SQ: HNSWSQConfig,
+    IndexType.HNSW_PQ: HNSWPQConfig,
+    IndexType.HNSW_PRQ: HNSWPRQConfig,
     IndexType.DISKANN: DISKANNConfig,
     IndexType.IVFFlat: IVFFlatConfig,
     IndexType.IVFSQ8: IVFSQ8Config,
+    IndexType.IVF_RABITQ: IVFRABITQConfig,
     IndexType.Flat: FLATConfig,
     IndexType.GPU_IVF_FLAT: GPUIVFFlatConfig,
     IndexType.GPU_IVF_PQ: GPUIVFPQConfig,
diff --git a/vectordb_bench/backend/clients/milvus/milvus.py b/vectordb_bench/backend/clients/milvus/milvus.py
index c812698fe..465c51179 100644
--- a/vectordb_bench/backend/clients/milvus/milvus.py
+++ b/vectordb_bench/backend/clients/milvus/milvus.py
@@ -61,6 +61,7 @@ def __init__(
                 consistency_level="Session",
             )
 
+            log.info(f"{self.name} create index: index_params: {self.case_config.index_param()}")
             col.create_index(
                 self._vector_field,
                 self.case_config.index_param(),
@@ -71,7 +72,7 @@ def __init__(
         connections.disconnect("default")
 
     @contextmanager
-    def init(self) -> None:
+    def init(self):
         """
         Examples:
             >>> with self.init():
@@ -126,6 +127,7 @@ def wait_index():
                 try:
                     self.col.compact()
                     self.col.wait_for_compaction_completed()
+                    log.info("compactation completed. waiting for the rest of index buliding.")
                 except Exception as e:
                     log.warning(f"{self.name} compact error: {e}")
                     if hasattr(e, "code"):
diff --git a/vectordb_bench/frontend/config/dbCaseConfigs.py b/vectordb_bench/frontend/config/dbCaseConfigs.py
index bb9cfa44b..bd59c3470 100644
--- a/vectordb_bench/frontend/config/dbCaseConfigs.py
+++ b/vectordb_bench/frontend/config/dbCaseConfigs.py
@@ -3,7 +3,7 @@
 from pydantic import BaseModel
 from vectordb_bench.backend.cases import CaseLabel, CaseType
 from vectordb_bench.backend.clients import DB
-from vectordb_bench.backend.clients.api import IndexType, MetricType
+from vectordb_bench.backend.clients.api import IndexType, MetricType, SQType
 from vectordb_bench.frontend.components.custom.getCustomConfig import get_custom_configs
 
 from vectordb_bench.models import CaseConfig, CaseConfigParamType
@@ -164,10 +164,13 @@ class CaseConfigInput(BaseModel):
     inputConfig={
         "options": [
             IndexType.HNSW.value,
+            IndexType.HNSW_SQ.value,
+            IndexType.HNSW_PQ.value,
+            IndexType.HNSW_PRQ.value,
             IndexType.IVFFlat.value,
             IndexType.IVFSQ8.value,
+            IndexType.IVF_RABITQ.value,
             IndexType.DISKANN.value,
-            IndexType.STREAMING_DISKANN.value,
             IndexType.Flat.value,
             IndexType.AUTOINDEX.value,
             IndexType.GPU_IVF_FLAT.value,
@@ -346,9 +349,16 @@ class CaseConfigInput(BaseModel):
         "max": 64,
         "value": 30,
     },
-    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) == IndexType.HNSW.value,
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [
+        IndexType.HNSW.value,
+        IndexType.HNSW_SQ.value,
+        IndexType.HNSW_PQ.value,
+        IndexType.HNSW_PRQ.value,
+    ],
 )
 
+
 CaseConfigParamInput_m = CaseConfigInput(
     label=CaseConfigParamType.m,
     inputType=InputType.Number,
@@ -369,7 +379,62 @@ class CaseConfigInput(BaseModel):
         "max": 512,
         "value": 360,
     },
-    isDisplayed=lambda config: config[CaseConfigParamType.IndexType] == IndexType.HNSW.value,
+    isDisplayed=lambda config: config[CaseConfigParamType.IndexType]
+    in [
+        IndexType.HNSW.value,
+        IndexType.HNSW_SQ.value,
+        IndexType.HNSW_PQ.value,
+        IndexType.HNSW_PRQ.value,
+    ],
+)
+
+CaseConfigParamInput_SQType = CaseConfigInput(
+    label=CaseConfigParamType.sq_type,
+    inputType=InputType.Option,
+    inputHelp="Scalar quantizer type.",
+    inputConfig={
+        "options": [SQType.SQ6.value, SQType.SQ8.value, SQType.BF16.value, SQType.FP16.value, SQType.FP32.value]
+    },
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) in [IndexType.HNSW_SQ.value],
+)
+
+CaseConfigParamInput_Refine = CaseConfigInput(
+    label=CaseConfigParamType.refine,
+    inputType=InputType.Option,
+    inputHelp="Whether refined data is reserved during index building.",
+    inputConfig={"options": [True, False]},
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [IndexType.HNSW_SQ.value, IndexType.HNSW_PQ.value, IndexType.HNSW_PRQ.value, IndexType.IVF_RABITQ.value],
+)
+
+CaseConfigParamInput_RefineType = CaseConfigInput(
+    label=CaseConfigParamType.refine_type,
+    inputType=InputType.Option,
+    inputHelp="The data type of the refine index.",
+    inputConfig={
+        "options": [SQType.FP32.value, SQType.FP16.value, SQType.BF16.value, SQType.SQ8.value, SQType.SQ6.value]
+    },
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [IndexType.HNSW_SQ.value, IndexType.HNSW_PQ.value, IndexType.HNSW_PRQ.value, IndexType.IVF_RABITQ.value]
+    and config.get(CaseConfigParamType.refine, True),
+)
+
+CaseConfigParamInput_RefineK = CaseConfigInput(
+    label=CaseConfigParamType.refine_k,
+    inputType=InputType.Float,
+    inputHelp="The magnification factor of refine compared to k.",
+    inputConfig={"min": 1.0, "max": 10000.0, "value": 1.0},
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [IndexType.HNSW_SQ.value, IndexType.HNSW_PQ.value, IndexType.HNSW_PRQ.value, IndexType.IVF_RABITQ.value]
+    and config.get(CaseConfigParamType.refine, True),
+)
+
+CaseConfigParamInput_RBQBitsQuery = CaseConfigInput(
+    label=CaseConfigParamType.rbq_bits_query,
+    inputType=InputType.Number,
+    inputHelp="The magnification factor of refine compared to k.",
+    inputConfig={"min": 0, "max": 8, "value": 0},
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) in [IndexType.IVF_RABITQ.value],
 )
 
 CaseConfigParamInput_EFConstruction_Weaviate = CaseConfigInput(
@@ -519,7 +584,13 @@ class CaseConfigInput(BaseModel):
         "max": MAX_STREAMLIT_INT,
         "value": 100,
     },
-    isDisplayed=lambda config: config[CaseConfigParamType.IndexType] == IndexType.HNSW.value,
+    isDisplayed=lambda config: config[CaseConfigParamType.IndexType]
+    in [
+        IndexType.HNSW.value,
+        IndexType.HNSW_SQ.value,
+        IndexType.HNSW_PQ.value,
+        IndexType.HNSW_PRQ.value,
+    ],
 )
 
 CaseConfigParamInput_EF_Weaviate = CaseConfigInput(
@@ -561,6 +632,7 @@ class CaseConfigInput(BaseModel):
     in [
         IndexType.IVFFlat.value,
         IndexType.IVFSQ8.value,
+        IndexType.IVF_RABITQ.value,
         IndexType.GPU_IVF_FLAT.value,
         IndexType.GPU_IVF_PQ.value,
         IndexType.GPU_BRUTE_FORCE.value,
@@ -579,6 +651,7 @@ class CaseConfigInput(BaseModel):
     in [
         IndexType.IVFFlat.value,
         IndexType.IVFSQ8.value,
+        IndexType.IVF_RABITQ.value,
         IndexType.GPU_IVF_FLAT.value,
         IndexType.GPU_IVF_PQ.value,
         IndexType.GPU_BRUTE_FORCE.value,
@@ -593,7 +666,8 @@ class CaseConfigInput(BaseModel):
         "max": 65536,
         "value": 0,
     },
-    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) in [IndexType.GPU_IVF_PQ.value],
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [IndexType.GPU_IVF_PQ.value, IndexType.HNSW_PQ.value, IndexType.HNSW_PRQ.value],
 )
 
 
@@ -605,7 +679,20 @@ class CaseConfigInput(BaseModel):
         "max": 65536,
         "value": 8,
     },
-    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) in [IndexType.GPU_IVF_PQ.value],
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None)
+    in [IndexType.GPU_IVF_PQ.value, IndexType.HNSW_PQ.value, IndexType.HNSW_PRQ.value],
+)
+
+CaseConfigParamInput_NRQ = CaseConfigInput(
+    label=CaseConfigParamType.nrq,
+    inputType=InputType.Number,
+    inputHelp="The number of residual subquantizers.",
+    inputConfig={
+        "min": 1,
+        "max": 16,
+        "value": 2,
+    },
+    isDisplayed=lambda config: config.get(CaseConfigParamType.IndexType, None) in [IndexType.HNSW_PRQ.value],
 )
 
 CaseConfigParamInput_intermediate_graph_degree = CaseConfigInput(
@@ -1186,6 +1273,10 @@ class CaseConfigInput(BaseModel):
     CaseConfigParamInput_graph_degree,
     CaseConfigParamInput_build_algo,
     CaseConfigParamInput_cache_dataset_on_device,
+    CaseConfigParamInput_SQType,
+    CaseConfigParamInput_Refine,
+    CaseConfigParamInput_RefineType,
+    CaseConfigParamInput_NRQ,
 ]
 MilvusPerformanceConfig = [
     CaseConfigParamInput_IndexType,
@@ -1197,6 +1288,8 @@ class CaseConfigInput(BaseModel):
     CaseConfigParamInput_Nprobe,
     CaseConfigParamInput_M_PQ,
     CaseConfigParamInput_Nbits_PQ,
+    CaseConfigParamInput_RBQBitsQuery,
+    CaseConfigParamInput_NRQ,
     CaseConfigParamInput_intermediate_graph_degree,
     CaseConfigParamInput_graph_degree,
     CaseConfigParamInput_itopk_size,
@@ -1207,6 +1300,10 @@ class CaseConfigInput(BaseModel):
     CaseConfigParamInput_build_algo,
     CaseConfigParamInput_cache_dataset_on_device,
     CaseConfigParamInput_refine_ratio,
+    CaseConfigParamInput_SQType,
+    CaseConfigParamInput_Refine,
+    CaseConfigParamInput_RefineType,
+    CaseConfigParamInput_RefineK,
 ]
 
 WeaviateLoadConfig = [
diff --git a/vectordb_bench/models.py b/vectordb_bench/models.py
index b28521096..ca00c4b55 100644
--- a/vectordb_bench/models.py
+++ b/vectordb_bench/models.py
@@ -55,6 +55,7 @@ class CaseConfigParamType(Enum):
     quantizedFetchLimit = "quantized_fetch_limit"
     m = "m"
     nbits = "nbits"
+    nrq = "nrq"
     intermediate_graph_degree = "intermediate_graph_degree"
     graph_degree = "graph_degree"
     itopk_size = "itopk_size"
@@ -65,6 +66,11 @@ class CaseConfigParamType(Enum):
     build_algo = "build_algo"
     cache_dataset_on_device = "cache_dataset_on_device"
     refine_ratio = "refine_ratio"
+    refine = "refine"
+    refine_type = "refine_type"
+    refine_k = "refine_k"
+    rbq_bits_query = "rbq_bits_query"
+    sq_type = "sq_type"
     level = "level"
     maintenance_work_mem = "maintenance_work_mem"
     max_parallel_workers = "max_parallel_workers"