diff --git a/Apache-Arrow-Flight-Tester/common.py b/Apache-Arrow-Flight-Tester/common.py
deleted file mode 100644
index 3608dbc..0000000
--- a/Apache-Arrow-Flight-Tester/common.py
+++ /dev/null
@@ -1,199 +0,0 @@
-import pyarrow
-import pprint
-
-from typing import Literal
-from protobuf import protocol_pb2
-from pyarrow import flight, Schema
-from pyarrow._flight import FlightInfo, ActionType, Result, Ticket
-
-
-class ModelarDBFlightClient:
-    """Common functionality for interacting with server and manager ModelarDB instances using Apache Arrow Flight."""
-
-    def __init__(self, location: str):
-        self.flight_client = flight.FlightClient(location)
-
-    def list_flights(self) -> list[FlightInfo]:
-        """Wrapper around the list_flights method of the FlightClient class."""
-        response = self.flight_client.list_flights()
-
-        return list(response)
-
-    def get_schema(self, table_name: str) -> Schema:
-        """Wrapper around the get_schema method of the FlightClient class."""
-        upload_descriptor = flight.FlightDescriptor.for_path(table_name)
-        response = self.flight_client.get_schema(upload_descriptor)
-
-        return response.schema
-
-    def do_get(self, ticket: Ticket) -> None:
-        """Wrapper around the do_get method of the FlightClient class."""
-        response = self.flight_client.do_get(ticket)
-
-        for batch in response:
-            pprint.pprint(batch.data.to_pydict())
-
-    def do_action(self, action_type: str, action_body: bytes) -> list[Result]:
-        """Wrapper around the do_action method of the FlightClient class."""
-        action = flight.Action(action_type, action_body)
-        response = self.flight_client.do_action(action)
-
-        return list(response)
-
-    def list_actions(self) -> list[ActionType]:
-        """Wrapper around the list_actions method of the FlightClient class."""
-        response = self.flight_client.list_actions()
-
-        return list(response)
-
-    def list_table_names(self) -> list[str]:
-        """Return the names of the tables in the server or manager."""
-        flights = self.list_flights()
-        return [table_name.decode("utf-8") for table_name in flights[0].descriptor.path]
-
-    def create_table(self, table_name: str, columns: list[tuple[str, str]], time_series_table=False) -> None:
-        """
-        Create a table in the server or manager with the given name and columns. Each pair in columns should have the
-        format (column_name, column_type).
-        """
-        create_table = (
-            "CREATE TIME SERIES TABLE" if time_series_table else "CREATE TABLE"
-        )
-        sql = f"{create_table} {table_name}({', '.join([f'{column[0]} {column[1]}' for column in columns])})"
-
-        self.do_get(Ticket(sql))
-
-    def create_test_tables(self) -> None:
-        """
-        Create a normal table and a time series table using the flight client, print the current tables to ensure the
-        created tables are included, and print the schema to ensure the tables are created correctly.
-        """
-        print("Creating test tables...")
-
-        self.create_table(
-            "test_table_1",
-            [("timestamp", "TIMESTAMP"), ("values", "REAL"), ("metadata", "REAL")],
-        )
-        self.create_table(
-            "test_time_series_table_1",
-            [
-                ("location", "TAG"),
-                ("install_year", "TAG"),
-                ("model", "TAG"),
-                ("timestamp", "TIMESTAMP"),
-                ("power_output", "FIELD"),
-                ("wind_speed", "FIELD"),
-                ("temperature", "FIELD(5%)"),
-            ],
-            time_series_table=True,
-        )
-
-        print("\nCurrent tables:")
-        for table_name in self.list_table_names():
-            print(f"{table_name}:")
-            print(f"{self.get_schema(table_name)}\n")
-
-    def create_normal_table_from_metadata(self, table_name: str, schema: pyarrow.Schema) -> None:
-        """Create a normal table using the table name and schema."""
-        normal_table_metadata = protocol_pb2.TableMetadata.NormalTableMetadata()
-
-        normal_table_metadata.name = table_name
-        normal_table_metadata.schema = schema.serialize().to_pybytes()
-
-        table_metadata = protocol_pb2.TableMetadata()
-        table_metadata.normal_table.CopyFrom(normal_table_metadata)
-
-        self.do_action("CreateTable", table_metadata.SerializeToString())
-
-    def create_time_series_table_from_metadata(self, table_name: str, schema: pyarrow.Schema, error_bounds: list[
-        protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound], generated_columns: list[bytes]) -> None:
-        """Create a time series table using the table name, schema, error bounds, and generated columns."""
-        time_series_table_metadata = protocol_pb2.TableMetadata.TimeSeriesTableMetadata()
-
-        time_series_table_metadata.name = table_name
-        time_series_table_metadata.schema = schema.serialize().to_pybytes()
-        time_series_table_metadata.error_bounds.extend(error_bounds)
-        time_series_table_metadata.generated_column_expressions.extend(generated_columns)
-
-        table_metadata = protocol_pb2.TableMetadata()
-        table_metadata.time_series_table.CopyFrom(time_series_table_metadata)
-
-        self.do_action("CreateTable", table_metadata.SerializeToString())
-
-    def create_test_tables_from_metadata(self):
-        """
-        Create a normal table and a time series table using the CreateTable action, print the current tables to ensure
-        the created tables are included, and print the schema to ensure the tables are created correctly.
-        """
-        print("Creating test tables from metadata...")
-
-        normal_table_schema = pyarrow.schema([
-            ("timestamp", pyarrow.timestamp("us")),
-            ("values", pyarrow.float32()),
-            ("metadata", pyarrow.utf8())
-        ])
-
-        self.create_normal_table_from_metadata("test_table_1", normal_table_schema)
-
-        time_series_table_schema = get_time_series_table_schema()
-
-        lossless = protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound.Type.LOSSLESS
-        error_bounds = [protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound(value=0, type=lossless)
-                        for _ in range(len(time_series_table_schema))]
-
-        generated_column_expressions = [b'' for _ in range(len(time_series_table_schema))]
-
-        self.create_time_series_table_from_metadata("test_time_series_table_1", time_series_table_schema,
-                                                    error_bounds, generated_column_expressions)
-
-        print("\nCurrent tables:")
-        for table_name in self.list_table_names():
-            print(f"{table_name}:")
-            print(f"{self.get_schema(table_name)}\n")
-
-    def drop_table(self, table_name: str) -> None:
-        """Drop the table with the given name from the server or manager."""
-        self.do_get(Ticket(f"DROP TABLE {table_name}"))
-
-    def truncate_table(self, table_name: str) -> None:
-        """Truncate the table with the given name in the server or manager."""
-        self.do_get(Ticket(f"TRUNCATE TABLE {table_name}"))
-
-    def clean_up_tables(self, tables: list[str], operation: Literal["drop", "truncate"]) -> None:
-        """
-        Clean up the given tables by either dropping them or truncating them. If no tables are given, all tables
-        are dropped or truncated.
-        """
-        if len(tables) == 0:
-            tables = self.list_table_names()
-
-        print(f"Cleaning up {', '.join(tables)} using {operation}...")
-
-        for table_name in tables:
-            (
-                self.drop_table(table_name)
-                if operation == "drop"
-                else self.truncate_table(table_name)
-            )
-
-    def vacuum(self, table_names: list[str]) -> None:
-        """Vacuum the given tables in the server or manager."""
-        self.do_get(Ticket(f"VACUUM {', '.join(table_names)}"))
-
-    def node_type(self) -> str:
-        """Return the type of the node."""
-        node_type = self.do_action("NodeType", b"")
-        return node_type[0].body.to_pybytes().decode("utf-8")
-
-
-def get_time_series_table_schema() -> pyarrow.Schema:
-    """Return a schema for a time series table with one timestamp column, three tag columns, and three field columns."""
-    return pyarrow.schema([
-        ("location", pyarrow.utf8()),
-        ("install_year", pyarrow.utf8()),
-        ("model", pyarrow.utf8()),
-        ("timestamp", pyarrow.timestamp("us")),
-        ("power_output", pyarrow.float32()),
-        ("wind_speed", pyarrow.float32()),
-        ("temperature", pyarrow.float32()),
-    ])
diff --git a/Apache-Arrow-Flight-Tester/manager.py b/Apache-Arrow-Flight-Tester/manager.py
deleted file mode 100644
index ce69227..0000000
--- a/Apache-Arrow-Flight-Tester/manager.py
+++ /dev/null
@@ -1,61 +0,0 @@
-from pyarrow import flight
-from pyarrow._flight import Result
-
-from common import ModelarDBFlightClient
-from protobuf import protocol_pb2
-from server import ModelarDBServerFlightClient
-
-
-class ModelarDBManagerFlightClient(ModelarDBFlightClient):
-    """Functionality for interacting with a ModelarDB manager using Apache Arrow Flight."""
-
-    def register_node(self, node_url: str,
-                      node_mode: protocol_pb2.NodeMetadata.ServerMode) -> protocol_pb2.ManagerMetadata:
-        """Register a node with the given URL and mode in the manager."""
-        node_metadata = protocol_pb2.NodeMetadata()
-        node_metadata.url = node_url
-        node_metadata.server_mode = node_mode
-
-        response = self.do_action("RegisterNode", node_metadata.SerializeToString())
-
-        manager_metadata = protocol_pb2.ManagerMetadata()
-        manager_metadata.ParseFromString(response[0].body.to_pybytes())
-
-        return manager_metadata
-
-    def remove_node(self, node_url: str) -> list[Result]:
-        """Remove the node with the given URL from the manager."""
-        node_metadata = protocol_pb2.NodeMetadata()
-        node_metadata.url = node_url
-
-        return self.do_action("RemoveNode", node_metadata.SerializeToString())
-
-    def query(self, query: str) -> None:
-        """
-        Retrieve a cloud node that can execute the given query and execute the query on the node. It is assumed that
-        at least one cloud node is already registered with the manager.
-        """
-        print("Retrieving cloud node that can execute the query...")
-        query_descriptor = flight.FlightDescriptor.for_command(query)
-        flight_info = self.flight_client.get_flight_info(query_descriptor)
-
-        endpoint = flight_info.endpoints[0]
-        cloud_node_url = endpoint.locations[0]
-
-        print(f"Executing query on {cloud_node_url}...")
-        cloud_client = ModelarDBServerFlightClient(cloud_node_url)
-        cloud_client.do_get(endpoint.ticket)
-
-
-if __name__ == "__main__":
-    manager_client = ModelarDBManagerFlightClient("grpc://127.0.0.1:9998")
-    print(f"Node type: {manager_client.node_type()}\n")
-
-    manager_client.create_test_tables_from_metadata()
-
-    print(manager_client.register_node("grpc://127.0.0.1:9999", protocol_pb2.NodeMetadata.ServerMode.EDGE))
-    print(manager_client.remove_node("grpc://127.0.0.1:9999"))
-
-    manager_client.query("SELECT * FROM test_time_series_table_1 LIMIT 5")
-
-    manager_client.clean_up_tables([], "drop")
diff --git a/Apache-Arrow-Flight-Tester/protobuf/protocol.proto b/Apache-Arrow-Flight-Tester/protobuf/protocol.proto
index 85242ac..d26b19e 100644
--- a/Apache-Arrow-Flight-Tester/protobuf/protocol.proto
+++ b/Apache-Arrow-Flight-Tester/protobuf/protocol.proto
@@ -17,47 +17,6 @@ syntax = "proto3";
 
 package modelardb.flight.protocol;
 
-// Metadata for the ModelarDB cluster manager, including its unique key and storage configuration.
-message ManagerMetadata {
-  // Key used to uniquely identify the cluster manager.
-  string key = 1;
-
-  // Storage configuration used to connect to an S3 object store.
-  message S3Configuration {
-    string endpoint = 1;
-    string bucket_name = 2;
-    string access_key_id = 3;
-    string secret_access_key = 4;
-  }
-
-  // Storage configuration used to connect to an Azure Blob Storage object store.
-  message AzureConfiguration {
-    string account_name = 1;
-    string access_key = 2;
-    string container_name = 3;
-  }
-
-  // Storage configuration used by the cluster manager.
-  oneof storage_configuration {
-    S3Configuration s3_configuration = 2;
-    AzureConfiguration azure_configuration = 3;
-  }
-}
-
-// Metadata for a node in the ModelarDB cluster, including its URL and server mode.
-message NodeMetadata {
-  enum ServerMode {
-    CLOUD = 0;
-    EDGE = 1;
-  }
-
-  // gRPC URL of the node.
-  string url = 1;
-
-  // Mode indicating whether the node is a cloud or edge server.
-  ServerMode server_mode = 2;
-}
-
 // Metadata for a normal table or a time series table.
 message TableMetadata {
   // Metadata for a normal table, including its name and schema.
diff --git a/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.py b/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.py
index 9d868a0..8ba9068 100644
--- a/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.py
+++ b/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.py
@@ -24,37 +24,27 @@
 
 
 
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0eprotocol.proto\x12\x19modelardb.flight.protocol\"\xb1\x03\n\x0fManagerMetadata\x12\x0b\n\x03key\x18\x01 \x01(\t\x12V\n\x10s3_configuration\x18\x02 \x01(\x0b\x32:.modelardb.flight.protocol.ManagerMetadata.S3ConfigurationH\x00\x12\\\n\x13\x61zure_configuration\x18\x03 \x01(\x0b\x32=.modelardb.flight.protocol.ManagerMetadata.AzureConfigurationH\x00\x1aj\n\x0fS3Configuration\x12\x10\n\x08\x65ndpoint\x18\x01 \x01(\t\x12\x13\n\x0b\x62ucket_name\x18\x02 \x01(\t\x12\x15\n\raccess_key_id\x18\x03 \x01(\t\x12\x19\n\x11secret_access_key\x18\x04 \x01(\t\x1aV\n\x12\x41zureConfiguration\x12\x14\n\x0c\x61\x63\x63ount_name\x18\x01 \x01(\t\x12\x12\n\naccess_key\x18\x02 \x01(\t\x12\x16\n\x0e\x63ontainer_name\x18\x03 \x01(\tB\x17\n\x15storage_configuration\"\x87\x01\n\x0cNodeMetadata\x12\x0b\n\x03url\x18\x01 \x01(\t\x12G\n\x0bserver_mode\x18\x02 \x01(\x0e\x32\x32.modelardb.flight.protocol.NodeMetadata.ServerMode\"!\n\nServerMode\x12\t\n\x05\x43LOUD\x10\x00\x12\x08\n\x04\x45\x44GE\x10\x01\"\xfe\x04\n\rTableMetadata\x12T\n\x0cnormal_table\x18\x01 \x01(\x0b\x32<.modelardb.flight.protocol.TableMetadata.NormalTableMetadataH\x00\x12]\n\x11time_series_table\x18\x02 \x01(\x0b\x32@.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadataH\x00\x1a\x33\n\x13NormalTableMetadata\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06schema\x18\x02 \x01(\x0c\x1a\xf0\x02\n\x17TimeSeriesTableMetadata\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06schema\x18\x02 \x01(\x0c\x12\x61\n\x0c\x65rror_bounds\x18\x03 \x03(\x0b\x32K.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadata.ErrorBound\x12$\n\x1cgenerated_column_expressions\x18\x04 \x03(\x0c\x1a\xad\x01\n\nErrorBound\x12^\n\x04type\x18\x01 \x01(\x0e\x32P.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadata.ErrorBound.Type\x12\r\n\x05value\x18\x02 \x01(\x02\"0\n\x04Type\x12\x0c\n\x08\x41\x42SOLUTE\x10\x00\x12\x0c\n\x08RELATIVE\x10\x01\x12\x0c\n\x08LOSSLESS\x10\x02\x42\x10\n\x0etable_metadata\"\xfa\x02\n\rConfiguration\x12-\n%multivariate_reserved_memory_in_bytes\x18\x01 \x01(\x04\x12-\n%uncompressed_reserved_memory_in_bytes\x18\x02 \x01(\x04\x12+\n#compressed_reserved_memory_in_bytes\x18\x03 \x01(\x04\x12)\n\x1ctransfer_batch_size_in_bytes\x18\x04 \x01(\x04H\x00\x88\x01\x01\x12%\n\x18transfer_time_in_seconds\x18\x05 \x01(\x04H\x01\x88\x01\x01\x12\x19\n\x11ingestion_threads\x18\x06 \x01(\r\x12\x1b\n\x13\x63ompression_threads\x18\x07 \x01(\r\x12\x16\n\x0ewriter_threads\x18\x08 \x01(\rB\x1f\n\x1d_transfer_batch_size_in_bytesB\x1b\n\x19_transfer_time_in_seconds\"\xcf\x02\n\x13UpdateConfiguration\x12G\n\x07setting\x18\x01 \x01(\x0e\x32\x36.modelardb.flight.protocol.UpdateConfiguration.Setting\x12\x16\n\tnew_value\x18\x02 \x01(\x04H\x00\x88\x01\x01\"\xc8\x01\n\x07Setting\x12)\n%MULTIVARIATE_RESERVED_MEMORY_IN_BYTES\x10\x00\x12)\n%UNCOMPRESSED_RESERVED_MEMORY_IN_BYTES\x10\x01\x12\'\n#COMPRESSED_RESERVED_MEMORY_IN_BYTES\x10\x02\x12 \n\x1cTRANSFER_BATCH_SIZE_IN_BYTES\x10\x03\x12\x1c\n\x18TRANSFER_TIME_IN_SECONDS\x10\x04\x42\x0c\n\n_new_valueb\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0eprotocol.proto\x12\x19modelardb.flight.protocol\"\xfe\x04\n\rTableMetadata\x12T\n\x0cnormal_table\x18\x01 \x01(\x0b\x32<.modelardb.flight.protocol.TableMetadata.NormalTableMetadataH\x00\x12]\n\x11time_series_table\x18\x02 \x01(\x0b\x32@.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadataH\x00\x1a\x33\n\x13NormalTableMetadata\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06schema\x18\x02 \x01(\x0c\x1a\xf0\x02\n\x17TimeSeriesTableMetadata\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06schema\x18\x02 \x01(\x0c\x12\x61\n\x0c\x65rror_bounds\x18\x03 \x03(\x0b\x32K.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadata.ErrorBound\x12$\n\x1cgenerated_column_expressions\x18\x04 \x03(\x0c\x1a\xad\x01\n\nErrorBound\x12^\n\x04type\x18\x01 \x01(\x0e\x32P.modelardb.flight.protocol.TableMetadata.TimeSeriesTableMetadata.ErrorBound.Type\x12\r\n\x05value\x18\x02 \x01(\x02\"0\n\x04Type\x12\x0c\n\x08\x41\x42SOLUTE\x10\x00\x12\x0c\n\x08RELATIVE\x10\x01\x12\x0c\n\x08LOSSLESS\x10\x02\x42\x10\n\x0etable_metadata\"\xfa\x02\n\rConfiguration\x12-\n%multivariate_reserved_memory_in_bytes\x18\x01 \x01(\x04\x12-\n%uncompressed_reserved_memory_in_bytes\x18\x02 \x01(\x04\x12+\n#compressed_reserved_memory_in_bytes\x18\x03 \x01(\x04\x12)\n\x1ctransfer_batch_size_in_bytes\x18\x04 \x01(\x04H\x00\x88\x01\x01\x12%\n\x18transfer_time_in_seconds\x18\x05 \x01(\x04H\x01\x88\x01\x01\x12\x19\n\x11ingestion_threads\x18\x06 \x01(\r\x12\x1b\n\x13\x63ompression_threads\x18\x07 \x01(\r\x12\x16\n\x0ewriter_threads\x18\x08 \x01(\rB\x1f\n\x1d_transfer_batch_size_in_bytesB\x1b\n\x19_transfer_time_in_seconds\"\xcf\x02\n\x13UpdateConfiguration\x12G\n\x07setting\x18\x01 \x01(\x0e\x32\x36.modelardb.flight.protocol.UpdateConfiguration.Setting\x12\x16\n\tnew_value\x18\x02 \x01(\x04H\x00\x88\x01\x01\"\xc8\x01\n\x07Setting\x12)\n%MULTIVARIATE_RESERVED_MEMORY_IN_BYTES\x10\x00\x12)\n%UNCOMPRESSED_RESERVED_MEMORY_IN_BYTES\x10\x01\x12\'\n#COMPRESSED_RESERVED_MEMORY_IN_BYTES\x10\x02\x12 \n\x1cTRANSFER_BATCH_SIZE_IN_BYTES\x10\x03\x12\x1c\n\x18TRANSFER_TIME_IN_SECONDS\x10\x04\x42\x0c\n\n_new_valueb\x06proto3')
 
 _globals = globals()
 _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
 _builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'protocol_pb2', _globals)
 if not _descriptor._USE_C_DESCRIPTORS:
   DESCRIPTOR._loaded_options = None
-  _globals['_MANAGERMETADATA']._serialized_start=46
-  _globals['_MANAGERMETADATA']._serialized_end=479
-  _globals['_MANAGERMETADATA_S3CONFIGURATION']._serialized_start=260
-  _globals['_MANAGERMETADATA_S3CONFIGURATION']._serialized_end=366
-  _globals['_MANAGERMETADATA_AZURECONFIGURATION']._serialized_start=368
-  _globals['_MANAGERMETADATA_AZURECONFIGURATION']._serialized_end=454
-  _globals['_NODEMETADATA']._serialized_start=482
-  _globals['_NODEMETADATA']._serialized_end=617
-  _globals['_NODEMETADATA_SERVERMODE']._serialized_start=584
-  _globals['_NODEMETADATA_SERVERMODE']._serialized_end=617
-  _globals['_TABLEMETADATA']._serialized_start=620
-  _globals['_TABLEMETADATA']._serialized_end=1258
-  _globals['_TABLEMETADATA_NORMALTABLEMETADATA']._serialized_start=818
-  _globals['_TABLEMETADATA_NORMALTABLEMETADATA']._serialized_end=869
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA']._serialized_start=872
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA']._serialized_end=1240
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND']._serialized_start=1067
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND']._serialized_end=1240
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND_TYPE']._serialized_start=1192
-  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND_TYPE']._serialized_end=1240
-  _globals['_CONFIGURATION']._serialized_start=1261
-  _globals['_CONFIGURATION']._serialized_end=1639
-  _globals['_UPDATECONFIGURATION']._serialized_start=1642
-  _globals['_UPDATECONFIGURATION']._serialized_end=1977
-  _globals['_UPDATECONFIGURATION_SETTING']._serialized_start=1763
-  _globals['_UPDATECONFIGURATION_SETTING']._serialized_end=1963
+  _globals['_TABLEMETADATA']._serialized_start=46
+  _globals['_TABLEMETADATA']._serialized_end=684
+  _globals['_TABLEMETADATA_NORMALTABLEMETADATA']._serialized_start=244
+  _globals['_TABLEMETADATA_NORMALTABLEMETADATA']._serialized_end=295
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA']._serialized_start=298
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA']._serialized_end=666
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND']._serialized_start=493
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND']._serialized_end=666
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND_TYPE']._serialized_start=618
+  _globals['_TABLEMETADATA_TIMESERIESTABLEMETADATA_ERRORBOUND_TYPE']._serialized_end=666
+  _globals['_CONFIGURATION']._serialized_start=687
+  _globals['_CONFIGURATION']._serialized_end=1065
+  _globals['_UPDATECONFIGURATION']._serialized_start=1068
+  _globals['_UPDATECONFIGURATION']._serialized_end=1403
+  _globals['_UPDATECONFIGURATION_SETTING']._serialized_start=1189
+  _globals['_UPDATECONFIGURATION_SETTING']._serialized_end=1389
 # @@protoc_insertion_point(module_scope)
diff --git a/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.pyi b/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.pyi
index e5b4de4..01f2fc5 100644
--- a/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.pyi
+++ b/Apache-Arrow-Flight-Tester/protobuf/protocol_pb2.pyi
@@ -7,50 +7,6 @@ from typing import ClassVar as _ClassVar, Optional as _Optional, Union as _Union
 
 DESCRIPTOR: _descriptor.FileDescriptor
 
-class ManagerMetadata(_message.Message):
-    __slots__ = ("key", "s3_configuration", "azure_configuration")
-    class S3Configuration(_message.Message):
-        __slots__ = ("endpoint", "bucket_name", "access_key_id", "secret_access_key")
-        ENDPOINT_FIELD_NUMBER: _ClassVar[int]
-        BUCKET_NAME_FIELD_NUMBER: _ClassVar[int]
-        ACCESS_KEY_ID_FIELD_NUMBER: _ClassVar[int]
-        SECRET_ACCESS_KEY_FIELD_NUMBER: _ClassVar[int]
-        endpoint: str
-        bucket_name: str
-        access_key_id: str
-        secret_access_key: str
-        def __init__(self, endpoint: _Optional[str] = ..., bucket_name: _Optional[str] = ..., access_key_id: _Optional[str] = ..., secret_access_key: _Optional[str] = ...) -> None: ...
-    class AzureConfiguration(_message.Message):
-        __slots__ = ("account_name", "access_key", "container_name")
-        ACCOUNT_NAME_FIELD_NUMBER: _ClassVar[int]
-        ACCESS_KEY_FIELD_NUMBER: _ClassVar[int]
-        CONTAINER_NAME_FIELD_NUMBER: _ClassVar[int]
-        account_name: str
-        access_key: str
-        container_name: str
-        def __init__(self, account_name: _Optional[str] = ..., access_key: _Optional[str] = ..., container_name: _Optional[str] = ...) -> None: ...
-    KEY_FIELD_NUMBER: _ClassVar[int]
-    S3_CONFIGURATION_FIELD_NUMBER: _ClassVar[int]
-    AZURE_CONFIGURATION_FIELD_NUMBER: _ClassVar[int]
-    key: str
-    s3_configuration: ManagerMetadata.S3Configuration
-    azure_configuration: ManagerMetadata.AzureConfiguration
-    def __init__(self, key: _Optional[str] = ..., s3_configuration: _Optional[_Union[ManagerMetadata.S3Configuration, _Mapping]] = ..., azure_configuration: _Optional[_Union[ManagerMetadata.AzureConfiguration, _Mapping]] = ...) -> None: ...
-
-class NodeMetadata(_message.Message):
-    __slots__ = ("url", "server_mode")
-    class ServerMode(int, metaclass=_enum_type_wrapper.EnumTypeWrapper):
-        __slots__ = ()
-        CLOUD: _ClassVar[NodeMetadata.ServerMode]
-        EDGE: _ClassVar[NodeMetadata.ServerMode]
-    CLOUD: NodeMetadata.ServerMode
-    EDGE: NodeMetadata.ServerMode
-    URL_FIELD_NUMBER: _ClassVar[int]
-    SERVER_MODE_FIELD_NUMBER: _ClassVar[int]
-    url: str
-    server_mode: NodeMetadata.ServerMode
-    def __init__(self, url: _Optional[str] = ..., server_mode: _Optional[_Union[NodeMetadata.ServerMode, str]] = ...) -> None: ...
-
 class TableMetadata(_message.Message):
     __slots__ = ("normal_table", "time_series_table")
     class NormalTableMetadata(_message.Message):
diff --git a/Apache-Arrow-Flight-Tester/server.py b/Apache-Arrow-Flight-Tester/server.py
index b7c7cfb..035520e 100644
--- a/Apache-Arrow-Flight-Tester/server.py
+++ b/Apache-Arrow-Flight-Tester/server.py
@@ -1,24 +1,86 @@
-import time
-from random import randrange
-
 import pyarrow
 from pyarrow import flight
 from pyarrow._flight import Result, Ticket
 
-from common import ModelarDBFlightClient, get_time_series_table_schema
+import util
+from wrapper import FlightClientWrapper
 from protobuf import protocol_pb2
 
 
-class ModelarDBServerFlightClient(ModelarDBFlightClient):
+class ModelarDBServerFlightClient(FlightClientWrapper):
     """Functionality for interacting with a ModelarDB server using Apache Arrow Flight."""
 
-    def do_put(self, table_name: str, record_batch: pyarrow.RecordBatch) -> None:
-        """Insert the data in the given record batch into the table with the given table name."""
-        upload_descriptor = flight.FlightDescriptor.for_path(table_name)
-        writer, _ = self.flight_client.do_put(upload_descriptor, record_batch.schema)
+    def list_table_names(self) -> list[str]:
+        """Return the names of the tables in the server."""
+        flights = self.list_flights()
+        return [table_name.decode("utf-8") for table_name in flights[0].descriptor.path]
+
+    def workload_balanced_query(self, query: str) -> None:
+        """
+        Retrieve a cloud node that can execute the given query and execute the query on the node. It is assumed that
+        the cluster has at least one cloud node.
+        """
+        print("Retrieving cloud node that can execute the query...")
+        query_descriptor = flight.FlightDescriptor.for_command(query)
+        flight_info = self.flight_client.get_flight_info(query_descriptor)
+
+        endpoint = flight_info.endpoints[0]
+        cloud_node_url = endpoint.locations[0]
+
+        print(f"Executing query on {cloud_node_url}...")
+        cloud_client = ModelarDBServerFlightClient(cloud_node_url)
+        cloud_client.do_get(endpoint.ticket)
+
+    def create_table(self, table_name: str, columns: list[tuple[str, str]], time_series_table=False) -> None:
+        """
+        Create a table in the server with the given name and columns. Each pair in columns should have the
+        format (column_name, column_type).
+        """
+        create_table = (
+            "CREATE TIME SERIES TABLE" if time_series_table else "CREATE TABLE"
+        )
+        sql = f"{create_table} {table_name}({', '.join([f'{column[0]} {column[1]}' for column in columns])})"
+
+        self.do_get(Ticket(sql))
+
+    def drop_tables(self, table_names: list[str]) -> None:
+        """Drop the given tables in the server."""
+        self.do_get(Ticket(f"DROP TABLE {', '.join(table_names)}"))
+
+    def truncate_tables(self, table_names: list[str]) -> None:
+        """Truncate the given tables in the server."""
+        self.do_get(Ticket(f"TRUNCATE {', '.join(table_names)}"))
+
+    def vacuum_tables(self, table_names: list[str]) -> None:
+        """Vacuum the given tables in the server."""
+        self.do_get(Ticket(f"VACUUM {', '.join(table_names)}"))
+
+    def create_normal_table_from_metadata(self, table_name: str, schema: pyarrow.Schema) -> None:
+        """Create a normal table using the table name and schema."""
+        normal_table_metadata = protocol_pb2.TableMetadata.NormalTableMetadata()
+
+        normal_table_metadata.name = table_name
+        normal_table_metadata.schema = schema.serialize().to_pybytes()
 
-        writer.write(record_batch)
-        writer.close()
+        table_metadata = protocol_pb2.TableMetadata()
+        table_metadata.normal_table.CopyFrom(normal_table_metadata)
+
+        self.do_action("CreateTable", table_metadata.SerializeToString())
+
+    def create_time_series_table_from_metadata(self, table_name: str, schema: pyarrow.Schema, error_bounds: list[
+        protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound], generated_columns: list[bytes]) -> None:
+        """Create a time series table using the table name, schema, error bounds, and generated columns."""
+        time_series_table_metadata = protocol_pb2.TableMetadata.TimeSeriesTableMetadata()
+
+        time_series_table_metadata.name = table_name
+        time_series_table_metadata.schema = schema.serialize().to_pybytes()
+        time_series_table_metadata.error_bounds.extend(error_bounds)
+        time_series_table_metadata.generated_column_expressions.extend(generated_columns)
+
+        table_metadata = protocol_pb2.TableMetadata()
+        table_metadata.time_series_table.CopyFrom(time_series_table_metadata)
+
+        self.do_action("CreateTable", table_metadata.SerializeToString())
 
     def get_configuration(self) -> protocol_pb2.Configuration:
         """Get the current configuration of the server."""
@@ -38,62 +100,22 @@ def update_configuration(self, setting: protocol_pb2.UpdateConfiguration.Setting
 
         return self.do_action("UpdateConfiguration", update_configuration.SerializeToString())
 
-    def ingest_into_server_and_query_table(self, table_name: str, num_rows: int) -> None:
-        """
-        Ingest num_rows rows into the table, flush the memory of the server, and query the first five rows of the table.
-        """
-        record_batch = create_record_batch(num_rows)
-
-        print(f"Ingesting data into {table_name}...\n")
-        self.do_put(table_name, record_batch)
-
-        print("Flushing memory of the edge...\n")
-        self.do_action("FlushMemory", b"")
-
-        print(f"First five rows of {table_name}:")
-        self.do_get(Ticket(f"SELECT * FROM {table_name} LIMIT 5"))
-
-
-def create_record_batch(num_rows: int) -> pyarrow.RecordBatch:
-    """
-    Create a record batch with num_rows rows of randomly generated data for a table with one timestamp column,
-    three tag columns, and three field columns.
-    """
-    schema = get_time_series_table_schema()
-
-    location = ["aalborg" if i % 2 == 0 else "nibe" for i in range(num_rows)]
-    install_year = ["2021" if i % 2 == 0 else "2022" for i in range(num_rows)]
-    model = ["w72" if i % 2 == 0 else "w73" for i in range(num_rows)]
-
-    timestamp = [round(time.time() * 1000000) + (i * 1000000) for i in range(num_rows)]
-    power_output = [float(randrange(0, 30)) for _ in range(num_rows)]
-    wind_speed = [float(randrange(50, 100)) for _ in range(num_rows)]
-    temperature = [float(randrange(0, 40)) for _ in range(num_rows)]
-
-    return pyarrow.RecordBatch.from_arrays(
-        [
-            location,
-            install_year,
-            model,
-            timestamp,
-            power_output,
-            wind_speed,
-            temperature,
-        ],
-        schema=schema,
-    )
+    def node_type(self) -> str:
+        """Return the type of the node."""
+        node_type = self.do_action("NodeType", b"")
+        return node_type[0].body.to_pybytes().decode("utf-8")
 
 
 if __name__ == "__main__":
     server_client = ModelarDBServerFlightClient("grpc://127.0.0.1:9999")
     print(f"Node type: {server_client.node_type()}\n")
 
-    server_client.create_test_tables()
-    server_client.ingest_into_server_and_query_table("test_time_series_table_1", 10000)
+    util.create_test_tables(server_client)
+    util.ingest_into_server_and_query_table(server_client, "test_time_series_table_1", 10000)
 
     print("\nCurrent configuration:")
     server_client.update_configuration(protocol_pb2.UpdateConfiguration.Setting.COMPRESSED_RESERVED_MEMORY_IN_BYTES,
                                        10000000)
     print(server_client.get_configuration())
 
-    server_client.clean_up_tables([], "drop")
+    util.clean_up_tables(server_client, [], "drop")
diff --git a/Apache-Arrow-Flight-Tester/util.py b/Apache-Arrow-Flight-Tester/util.py
new file mode 100644
index 0000000..758562a
--- /dev/null
+++ b/Apache-Arrow-Flight-Tester/util.py
@@ -0,0 +1,149 @@
+import time
+from random import randrange
+from typing import Literal
+
+import pyarrow
+from protobuf import protocol_pb2
+from pyarrow._flight import Ticket
+
+from server import ModelarDBServerFlightClient
+
+
+def create_record_batch(num_rows: int) -> pyarrow.RecordBatch:
+    """
+    Create a record batch with num_rows rows of randomly generated data for a table with one timestamp column,
+    three tag columns, and three field columns.
+    """
+    schema = get_time_series_table_schema()
+
+    location = ["aalborg" if i % 2 == 0 else "nibe" for i in range(num_rows)]
+    install_year = ["2021" if i % 2 == 0 else "2022" for i in range(num_rows)]
+    model = ["w72" if i % 2 == 0 else "w73" for i in range(num_rows)]
+
+    timestamp = [round(time.time() * 1000000) + (i * 1000000) for i in range(num_rows)]
+    power_output = [float(randrange(0, 30)) for _ in range(num_rows)]
+    wind_speed = [float(randrange(50, 100)) for _ in range(num_rows)]
+    temperature = [float(randrange(0, 40)) for _ in range(num_rows)]
+
+    return pyarrow.RecordBatch.from_arrays(
+        [
+            location,
+            install_year,
+            model,
+            timestamp,
+            power_output,
+            wind_speed,
+            temperature,
+        ],
+        schema=schema,
+    )
+
+
+def get_time_series_table_schema() -> pyarrow.Schema:
+    """Return a schema for a time series table with one timestamp column, three tag columns, and three field columns."""
+    return pyarrow.schema([
+        ("location", pyarrow.utf8()),
+        ("install_year", pyarrow.utf8()),
+        ("model", pyarrow.utf8()),
+        ("timestamp", pyarrow.timestamp("us")),
+        ("power_output", pyarrow.float32()),
+        ("wind_speed", pyarrow.float32()),
+        ("temperature", pyarrow.float32()),
+    ])
+
+
+def create_test_tables(server_client: ModelarDBServerFlightClient) -> None:
+    """
+    Create a normal table and a time series table using the flight client, print the current tables to ensure the
+    created tables are included, and print the schema to ensure the tables are created correctly.
+    """
+    print("Creating test tables...")
+
+    server_client.create_table(
+        "test_table_1",
+        [("timestamp", "TIMESTAMP"), ("values", "REAL"), ("metadata", "REAL")],
+    )
+    server_client.create_table(
+        "test_time_series_table_1",
+        [
+            ("location", "TAG"),
+            ("install_year", "TAG"),
+            ("model", "TAG"),
+            ("timestamp", "TIMESTAMP"),
+            ("power_output", "FIELD"),
+            ("wind_speed", "FIELD"),
+            ("temperature", "FIELD(5%)"),
+        ],
+        time_series_table=True,
+    )
+
+    print("\nCurrent tables:")
+    for table_name in server_client.list_table_names():
+        print(f"{table_name}:")
+        print(f"{server_client.get_schema(table_name)}\n")
+
+
+def create_test_tables_from_metadata(server_client: ModelarDBServerFlightClient) -> None:
+    """
+    Create a normal table and a time series table using the CreateTable action, print the current tables to ensure
+    the created tables are included, and print the schema to ensure the tables are created correctly.
+    """
+    print("Creating test tables from metadata...")
+
+    normal_table_schema = pyarrow.schema([
+        ("timestamp", pyarrow.timestamp("us")),
+        ("values", pyarrow.float32()),
+        ("metadata", pyarrow.utf8())
+    ])
+
+    server_client.create_normal_table_from_metadata("test_table_1", normal_table_schema)
+
+    time_series_table_schema = get_time_series_table_schema()
+
+    lossless = protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound.Type.LOSSLESS
+    error_bounds = [protocol_pb2.TableMetadata.TimeSeriesTableMetadata.ErrorBound(value=0, type=lossless)
+                    for _ in range(len(time_series_table_schema))]
+
+    generated_column_expressions = [b'' for _ in range(len(time_series_table_schema))]
+
+    server_client.create_time_series_table_from_metadata("test_time_series_table_1", time_series_table_schema,
+                                                         error_bounds, generated_column_expressions)
+
+    print("\nCurrent tables:")
+    for table_name in server_client.list_table_names():
+        print(f"{table_name}:")
+        print(f"{server_client.get_schema(table_name)}\n")
+
+
+def ingest_into_server_and_query_table(server_client: ModelarDBServerFlightClient, table_name: str,
+                                       num_rows: int) -> None:
+    """
+    Ingest num_rows rows into the table, flush the memory of the server, and query the first five rows of the table.
+    """
+    record_batch = create_record_batch(num_rows)
+
+    print(f"Ingesting data into {table_name}...\n")
+    server_client.do_put(table_name, record_batch)
+
+    print("Flushing memory of the node...\n")
+    server_client.do_action("FlushMemory", b"")
+
+    print(f"First five rows of {table_name}:")
+    server_client.do_get(Ticket(f"SELECT * FROM {table_name} LIMIT 5"))
+
+
+def clean_up_tables(server_client: ModelarDBServerFlightClient, tables: list[str],
+                    operation: Literal["drop", "truncate"]) -> None:
+    """
+    Clean up the given tables by either dropping them or truncating them. If no tables are given, all tables
+    are dropped or truncated.
+    """
+    if len(tables) == 0:
+        tables = server_client.list_table_names()
+
+    print(f"Cleaning up {', '.join(tables)} using {operation}...")
+
+    if operation == "drop":
+        server_client.drop_tables(tables)
+    else:
+        server_client.truncate_tables(tables)
diff --git a/Apache-Arrow-Flight-Tester/wrapper.py b/Apache-Arrow-Flight-Tester/wrapper.py
new file mode 100644
index 0000000..c8f2142
--- /dev/null
+++ b/Apache-Arrow-Flight-Tester/wrapper.py
@@ -0,0 +1,53 @@
+import pyarrow
+import pprint
+
+from pyarrow import flight, Schema
+from pyarrow._flight import FlightInfo, ActionType, Result, Ticket
+
+
+class FlightClientWrapper:
+    """Wrapper around the FlightClient class to simplify interaction with an Apache Arrow Flight server."""
+
+    def __init__(self, location: str):
+        self.flight_client = flight.FlightClient(location)
+
+    def list_flights(self) -> list[FlightInfo]:
+        """Wrapper around the list_flights method of the FlightClient class."""
+        response = self.flight_client.list_flights()
+
+        return list(response)
+
+    def get_schema(self, table_name: str) -> Schema:
+        """Wrapper around the get_schema method of the FlightClient class."""
+        upload_descriptor = flight.FlightDescriptor.for_path(table_name)
+        response = self.flight_client.get_schema(upload_descriptor)
+
+        return response.schema
+
+    def do_get(self, ticket: Ticket) -> None:
+        """Wrapper around the do_get method of the FlightClient class."""
+        response = self.flight_client.do_get(ticket)
+
+        for batch in response:
+            pprint.pprint(batch.data.to_pydict())
+
+    def do_put(self, table_name: str, record_batch: pyarrow.RecordBatch) -> None:
+        """Wrapper around the do_put method of the FlightClient class."""
+        upload_descriptor = flight.FlightDescriptor.for_path(table_name)
+        writer, _ = self.flight_client.do_put(upload_descriptor, record_batch.schema)
+
+        writer.write(record_batch)
+        writer.close()
+
+    def do_action(self, action_type: str, action_body: bytes) -> list[Result]:
+        """Wrapper around the do_action method of the FlightClient class."""
+        action = flight.Action(action_type, action_body)
+        response = self.flight_client.do_action(action)
+
+        return list(response)
+
+    def list_actions(self) -> list[ActionType]:
+        """Wrapper around the list_actions method of the FlightClient class."""
+        response = self.flight_client.list_actions()
+
+        return list(response)
diff --git a/README.md b/README.md
index 65a7941..2854452 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,6 @@
 # Utilities
 Utilities for simplifying development and testing developed in this repository:
 
-- [Apache Arrow Flight manager testing](Apache-Arrow-Flight-Tester/manager.py) is a script written in
-  [Python 3](https://www.python.org/) to test the different endpoints of the ModelarDB manager Apache Arrow Flight API.
-
 - [Apache Arrow Flight server testing](Apache-Arrow-Flight-Tester/server.py) is a script written in
   [Python 3](https://www.python.org/) to test the different endpoints of the ModelarDB server Apache Arrow Flight API.