In this lesson, you will learn how to choose between Serializability and Snapshot Isolation to maintain data integrity when transactions span multiple distributed nodes.
When your data is partitioned across several physical nodes, ensuring that concurrent operations don't corrupt the system state becomes significantly more complex than in a single-instance database. Two primary isolation levels emerge as industry standards for handling these distributed race conditions: Serializability and Snapshot Isolation.
The Core Difference
Serializability is the gold standard for correctness. It guarantees that the outcome of executing multiple transactions concurrently is exactly the same as if they were executed one after the other (serially). In a distributed context, this requires coordination across nodes—often via consensus algorithms like Paxos or Raft—to lock resources or order transaction timestamps. While it prevents all anomalies (including phantom reads and write skews), the overhead of cross-node synchronization can significantly increase latency.
Snapshot Isolation (SI) offers a performance-oriented alternative. Instead of locking, each transaction operates on a consistent "snapshot" of the database taken at its start time. When a transaction commits, the system checks if any data it modified was updated by another transaction since that snapshot was taken. If a conflict is detected, the transaction aborts.
Illustrative Conflict: The Write Skew
Consider a distributed banking system where a rule states the sum of two accounts (A + B) must be at least $100.
- Node 1 reads
A = 60, Node 2 readsB = 60. - Both nodes see the total is $120, satisfying the rule.
- Node 1 subtracts 30 from
B. - Both commit. Total is now $60, violating the rule.
A Serializable system would detect this dependency and force one transaction to wait or fail. Snapshot Isolation, however, might allow this "write skew" because the two transactions modified different rows, even though they logically conflicted based on the business constraint.
-- Transaction A (Node 1) & Transaction B (Node 2)
-- Under Snapshot Isolation, both see the same state and neither
-- locks the other, leading to a potential write skew.
SELECT balance FROM accounts WHERE id = 'A'; -- Returns 60
SELECT balance FROM accounts WHERE id = 'B'; -- Returns 60
UPDATE accounts SET balance = 30 WHERE id = 'A';
UPDATE accounts SET balance = 30 WHERE id = 'B';
Key Takeaway: Choose Serializability when absolute correctness is mandatory for business logic, and use Snapshot Isolation when you need to balance performance with a high—but not perfect—degree of data consistency.