Transactions
Run multiple operations that succeed or fail together. If any operation fails, DynamoDB rolls back all changes automatically.
Key features
- All-or-nothing operations
- Put, delete, update, and read in one transaction
- Max 100 items per transaction
- Metrics on every operation (see observability)
Getting started
Transactions are useful when you need to update related data atomically. For example, when creating an order, you might want to:
- Create the order record
- Update the user's order count
- Decrease inventory
If any of these fails, you don't want partial data. Transactions guarantee all operations succeed or none do.
import asyncio
from pydynox import DynamoDBClient, Transaction
client = DynamoDBClient()
async def create_order():
async with Transaction(client) as tx:
tx.put("users", {"pk": "USER#1", "sk": "PROFILE", "name": "John"})
tx.put("orders", {"pk": "ORDER#1", "sk": "DETAILS", "user": "USER#1"})
asyncio.run(create_order())
When you use Transaction as a context manager, it automatically commits when the block ends. If an exception occurs inside the block, the transaction is not committed.
Reading multiple items
Use transact_get to read multiple items atomically. This gives you a consistent snapshot - all items are read at the same point in time.
import asyncio
from pydynox import DynamoDBClient
client = DynamoDBClient()
async def get_order_details():
items = await client.transact_get(
[
{"table": "users", "key": {"pk": "USER#1", "sk": "PROFILE"}},
{"table": "orders", "key": {"pk": "ORDER#1", "sk": "DETAILS"}},
]
)
user, order = items
print(f"User: {user}, Order: {order}")
asyncio.run(get_order_details())
This is useful when you need to read related data that must be consistent. For example, reading a user and their orders together.
Writing with client methods
You can also use transact_write directly for more complex operations:
import asyncio
from pydynox import DynamoDBClient
client = DynamoDBClient()
async def create_user_and_order():
operations = [
{
"type": "put",
"table": "users",
"item": {"pk": "USER#1", "sk": "PROFILE", "name": "John"},
},
{
"type": "put",
"table": "orders",
"item": {"pk": "ORDER#1", "sk": "DETAILS", "user": "USER#1", "total": 100},
},
]
await client.transact_write(operations)
asyncio.run(create_user_and_order())
API reference
Transaction class
| Method | Description |
|---|---|
tx.put(table, item) |
Add or replace an item |
tx.delete(table, key) |
Remove an item |
tx.update(table, key, updates) |
Update specific attributes |
tx.condition_check(table, key, condition) |
Check a condition without modifying |
Client methods
| Async (default) | Sync | Description |
|---|---|---|
await client.transact_write(ops) |
client.sync_transact_write(ops) |
Write multiple items atomically |
await client.transact_get(gets) |
client.sync_transact_get(gets) |
Read multiple items atomically |
Classes
| Async (default) | Sync | Description |
|---|---|---|
Transaction |
SyncTransaction |
Context manager for transactions |
Limits
DynamoDB transactions have limits you should know:
| Limit | Value |
|---|---|
| Max items | 100 |
| Max size | 4 MB total |
| Region | All items must be in the same region |
If you exceed these limits, the transaction fails before any operation runs.
When to use transactions
Use transactions when:
- You need all-or-nothing behavior
- You're updating related data that must stay consistent
- You need to check conditions before writing (like "only update if version matches")
- You need a consistent snapshot of multiple items
Don't use transactions for:
- Simple single-item operations (just use
save()) - High-throughput batch writes (use
BatchWriterinstead - it's faster) - Operations that can tolerate partial success
Tip
Transactions cost twice as much as regular operations because DynamoDB does extra work to guarantee atomicity. Use them only when you need the guarantee.
Error handling
If a transaction fails, DynamoDB returns an error and no changes are made:
import asyncio
from pydynox import DynamoDBClient, Transaction
from pydynox.exceptions import TransactionCanceledException
client = DynamoDBClient()
async def safe_transfer():
try:
async with Transaction(client) as tx:
tx.put("users", {"pk": "USER#1", "name": "John"})
tx.put("orders", {"pk": "ORDER#1", "user": "USER#1"})
except TransactionCanceledException as e:
print(f"Transaction canceled: {e}")
except Exception as e:
print(f"Transaction failed: {e}")
asyncio.run(safe_transfer())
Common reasons for transaction failures:
- Item size exceeds 400 KB
- Total transaction size exceeds 4 MB
- More than 100 items
- Condition check failed
- Throughput exceeded
Sync API
For sync code, use SyncTransaction and the sync_ prefixed methods:
from pydynox import DynamoDBClient, SyncTransaction
client = DynamoDBClient()
with SyncTransaction(client) as tx:
tx.put("users", {"pk": "USER#1", "sk": "PROFILE", "name": "John"})
tx.put("orders", {"pk": "ORDER#1", "sk": "DETAILS", "user": "USER#1"})
# Direct client method
items = client.sync_transact_get(
[
{"table": "users", "key": {"pk": "USER#1", "sk": "PROFILE"}},
]
)
Next steps
- Tables - Create and manage tables
- Conditions - Add conditions to transactions
- Exceptions - Handle transaction errors