diff --git a/Project.toml b/Project.toml
index 6e3945f..d2d61e8 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "NATSBridge"
 uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
-version = "0.5.3"
+version = "0.5.4"
 authors = ["narawat <narawat@gmail.com>"]
 
 [deps]
diff --git a/src/NATSBridge.jl b/src/NATSBridge.jl
index 938971a..fd152f5 100644
--- a/src/NATSBridge.jl
+++ b/src/NATSBridge.jl
@@ -931,8 +931,8 @@ It handles "text" (string), "dictionary" (JSON deserialization), "arrowtable" (A
 2. Converts bytes to appropriate Julia data type based on format
 3. For text: converts bytes to string
 4. For dictionary: converts bytes to JSON string then parses to Julia object
-5. For arrowtable: reads Arrow IPC format and returns Arrow.Table
-6. For jsontable: converts bytes to JSON string then parses to Vector{Dict}
+5. For arrowtable: reads Arrow IPC format and returns a DataFrame
+6. For jsontable: converts bytes to JSON string then parses to Vector{Dict} and return a DataFrame
 7. For image/audio/video/binary: returns bytes directly
 
 # Arguments:
@@ -958,11 +958,11 @@ json_data = _deserialize_data(json_bytes, "dictionary", "correlation123")
 
 # Arrow IPC data (arrowtable)
 arrow_bytes = Vector{UInt8}([1, 2, 3])  # Arrow IPC bytes
-arrow_table = _deserialize_data(arrow_bytes, "arrowtable", "correlation123")
+df = _deserialize_data(arrow_bytes, "arrowtable", "correlation123")
 
 # JSON table data (jsontable)
 json_table_bytes = UInt8[91, 123, 34, 105, 100, 34, 58, 49, 44, 34, 110, 97, 109, 101, 34, 58, 34, 65, 108, 105, 99, 101, 34, 125]  # [{"id":1,"name":"Alice"}]
-json_table = _deserialize_data(json_table_bytes, "jsontable", "correlation123")
+df = _deserialize_data(json_table_bytes, "jsontable", "correlation123")
 ```
 """
 function _deserialize_data(
@@ -977,11 +977,14 @@ function _deserialize_data(
     return JSON.parse(json_str)  # Parse JSON string to JSON object
   elseif payload_type == "arrowtable"  # Arrow table data - deserialize Arrow IPC stream
     io = IOBuffer(data)  # Create buffer from bytes
-    table = Arrow.Table(io)  # Read Arrow IPC format from buffer
-    return table  # Return Arrow.Table
+    arrowtable = Arrow.Table(io)  # Read Arrow IPC format from buffer
+    df = DataFrame(arrowtable)
+    return df
   elseif payload_type == "jsontable"  # JSON table data - deserialize JSON
     json_str = String(data)  # Convert bytes to string
-    return JSON.parse(json_str)  # Parse JSON string to Vector{Dict}
+    jsontable = JSON.parse(json_str)  # Parse JSON string to jsontable i.e. Vector{Dict}
+    df = DataFrame(jsontable)
+    return df
   elseif payload_type == "image"  # Image data - return binary
     return data  # Return bytes directly
   elseif payload_type == "audio"  # Audio data - return binary