Python Database API Driver

GridGain 9 clients connect to the cluster via a standard socket connection. Clients do not become a part of the cluster topology, never hold any data, and are not used as a destination for compute calculations.

GridGain DB API driver uses the Python Database API.

Getting Started

Prerequisites

To run the Python driver, the following is required:

CMake 3.18 or newer to build the driver
Python 3.10 or newer (3.10, 3.11, 3.12, 3.13 and 3.14 are tested)
Access to a running Ignite 3 or GridGain 9 node

Limitations

Script execution of SQL statements is not supported in current release.

Installation

To install Python DB API driver, download it from pip.

pip install pygridgain_dbapi

After this, you can import pygridgain_dbapi into your project and use it.

Connecting to Cluster

To connect to the cluster, use the connect() method:

addr = ['127.0.0.1:10800']
return pygridgain_dbapi.connect(address=addr, timeout=10)

Connection Parameters

The connect() function accepts the following parameters:

Parameter Type Description

Parameter	Type	Description
address	str or list[str]	Required. Cluster node address(es) for initial connection and fail-over. Examples: `'localhost:10800'` or `['host1:10800', 'host2:10800']`
identity	str	Username for authentication. Used with `secret` for basic authentication.
secret	str	Password for authentication. Used with `identity` for basic authentication.
schema	str	Default schema name. Default: `'PUBLIC'`
timezone	str	Client timezone for date/time operations. Default: server timezone
page_size	int	Maximum rows per request. Default: `1024`
timeout	int	Network operation timeout in seconds. Default: `30`
heartbeat_interval	float	Heartbeat interval in seconds. Set to 0 to disable. Default: `30.0`
autocommit	bool	Enable automatic transaction commit. Default: `True`
use_ssl	bool	Enable SSL/TLS encryption. Default: `False`
ssl_keyfile	str	Path to SSL key file. Required if `use_ssl=True` and using client authentication.
ssl_certfile	str	Path to SSL certificate file. Required if `use_ssl=True` and using client authentication.
ssl_ca_certfile	str	Path to CA certificate for server validation. Required if `use_ssl=True`.

address

str or list[str]

Required. Cluster node address(es) for initial connection and fail-over. Examples: 'localhost:10800' or ['host1:10800', 'host2:10800']

identity

str

Username for authentication. Used with secret for basic authentication.

secret

str

Password for authentication. Used with identity for basic authentication.

schema

str

Default schema name. Default: 'PUBLIC'

timezone

str

Client timezone for date/time operations. Default: server timezone

page_size

int

Maximum rows per request. Default: 1024

timeout

int

Network operation timeout in seconds. Default: 30

heartbeat_interval

float

Heartbeat interval in seconds. Set to 0 to disable. Default: 30.0

autocommit

bool

Enable automatic transaction commit. Default: True

use_ssl

bool

Enable SSL/TLS encryption. Default: False

ssl_keyfile

str

Path to SSL key file. Required if use_ssl=True and using client authentication.

ssl_certfile

str

Path to SSL certificate file. Required if use_ssl=True and using client authentication.

ssl_ca_certfile

str

Path to CA certificate for server validation. Required if use_ssl=True.

After you are done working with the cluster, remember to always close the connection to it.

conn.close()

Alternatively, you can use the with statement to automatically close the connection when no longer necessary:

with pygridgain_dbapi.connect(address=addr, timeout=10) as conn:
  conn.cursor()

Configuring SSL for Connection

To ensure secure connection to the cluster, you can enable SSL for it by providing the key file and certificate, for example:

def create_ssl_connection():
  """Create SSL-enabled connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return pygridgain_dbapi.connect(
      address=addr,
      timeout=10,
      use_ssl=True,
      ssl_keyfile='<path_to_ssl_keyfile.pem>',
      ssl_certfile='<path_to_ssl_certfile.pem>',
      # Optional: ssl_ca_certfile='<path_to_ssl_ca_certfile.pem>'
  )

Configuring Authorization

If the cluster uses basic authorization, you need to provide user identity and secret to authorize on it, for example:

def create_authenticated_connection():
  """Create authenticated connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return pygridgain_dbapi.connect(
      address=addr,
      timeout=10,
      identity='user',
      secret='password'
  )

Configuring Data Access

You can configure optional properties to fine-tune how data is accessed and how the connection behaves.

Configuration name	Default	Description
schema	'PUBLIC'	A schema name to be used by default.
page_size	1024	Maximum number of rows that can be received or sent in a single request.
timeout	30	Timeout for network operations, in seconds.
heartbeat_interval	30.0	Interval between heartbeat probes, in seconds. Set to 0 or negative to disable heartbeats. See Connection Heartbeats for details.
timezone	(server)	Client’s timezone. Required to correctly work with date/time values. By default, server’s timezone is used.

Configuration name

Default

Description

schema

'PUBLIC'

A schema name to be used by default.

page_size

1024

Maximum number of rows that can be received or sent in a single request.

timeout

Timeout for network operations, in seconds.

heartbeat_interval

30.0

Interval between heartbeat probes, in seconds. Set to 0 or negative to disable heartbeats. See Connection Heartbeats for details.

timezone

(server)

Client’s timezone. Required to correctly work with date/time values. By default, server’s timezone is used.

The example below shows how to set these properties:

def create_configured_connection():
  """Create authenticated connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return conn = pygridgain_dbapi.connect(
    address=addr,
    timeout=10,
    schema='CUSTOM',
    page_size=2048
  )

Connection Heartbeats

The Python DB API driver supports connection heartbeats to prevent the server from closing idle connections. When enabled, the driver automatically sends periodic heartbeat messages to the server during periods of inactivity.

The driver tracks when the last message was sent to the server. If the connection is idle for longer than the heartbeat_interval, a heartbeat message is sent. If other queries or operations are executed, no heartbeat is needed. Heartbeats keep the connection alive without requiring application changes.

By default, heartbeats are sent every 30 seconds. You can customize the heartbeat interval or disable it by setting the interval to 0:

# Custom heartbeat interval (10 seconds)
conn = pyignite_dbapi.connect(
    address='localhost:10800',
    heartbeat_interval=10.0
)

# Disable heartbeats
conn = pyignite_dbapi.connect(
    address='localhost:10800',
    heartbeat_interval=0
)

Getting Cursor Object

To work with tables from Python client, you use the cursor object that can be retrieved from the connection object:

conn.cursor()

Similar to the connection, you can use the with statement when getting the cursor:

with conn.cursor() as cursor:

Executing Single Query

The cursor object can be used to execute SQL statements with the execute command:

# Create table
cursor.execute('''
          CREATE TABLE Person(
              id INT PRIMARY KEY, 
              name VARCHAR, 
              age INT
          )
      ''')

Executing a Batched Query

You can use the executemany command to execute SQL queries with a batch of parameters. This kind of operation offers much higher performance than executing individual queries. The example below inserts two rows into the Person table:

# Sample data
sample_data = [
  [1, "John", 30],
  [2, "Jane", 32],
  [3, "Bob", 28]
]

# Insert data (fixed table name)
cursor.executemany('INSERT INTO Person VALUES(?, ?, ?)', sample_data)

Getting Query Results

The cursor retains a reference to the operation. If the operation returns results (for example, a SELECT), they will also be stored in the cursor. You can then use the fetchone() method to retrieve query results from the cursor:

# Query data
cursor.execute('SELECT * FROM Person ORDER BY id')
results = cursor.fetchall()

print("All persons in database:")
for row in results:
  print(f"ID: {row[0]}, Name: {row[1]}, Age: {row[2]}")

Working with Transactions

By default, transactions required for database operations are handled implicitly. However, you can disable automatic transaction handling and manually handle commits.

To do this, first, disable autocommit:

conn.autocommit = False

Once autocommit is disabled, you need to commit your operations manually:

# Insert valid records
cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [4, "Alice", 29])
cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [5, "Charlie", 31])


cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [6, "Invalid", new_age])

conn.commit()
print("Transaction committed successfully")

Operations that are not committed are sent to the cluster, but not yet written to the table. The table is only updated when the commit method is called. You can roll back all uncommitted operations with the rollback command:

with conn.cursor() as cursor:
  try:
    # Insert valid records
    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [4, "Alice", 29])
    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [5, "Charlie", 31])


    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [6, "Invalid", new_age])

    conn.commit()
    print("Transaction committed successfully")

  except Exception as e:
    # Rollback on any error
    conn.rollback()
    print(f"Transaction rolled back due to error: {e}")

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Last updated on Mar 06, 2026