How do document databases handle ACID transactions?

Document databases handle ACID transactions by implementing mechanisms that ensure atomicity, consistency, isolation, and durability, though the level of support varies across systems. While traditional NoSQL databases prioritized scalability over strict transactional guarantees, modern document databases like MongoDB and Couchbase now offer ACID-compliant transactions for multi-document operations. For example, MongoDB introduced multi-document ACID transactions in version 4.0, allowing developers to group operations across multiple documents into a single transaction. This ensures that either all operations succeed (atomicity) or the transaction rolls back entirely, maintaining data consistency even in distributed environments.

The mechanics of ACID in document databases typically involve a combination of write-ahead logging, snapshot isolation, and distributed consensus protocols. MongoDB, for instance, uses a two-phase commit protocol for distributed transactions, where changes are first staged and then finalized across nodes. During a transaction, the database creates a snapshot of the data, ensuring isolation so concurrent transactions don’t interfere. For durability, changes are written to a transaction log before being acknowledged to the client. However, there are limitations: document databases may restrict transaction scope (e.g., MongoDB limits transaction duration to 60 seconds by default) or require careful schema design to avoid performance bottlenecks. Single-document operations, like updating nested fields, remain atomic without explicit transactions due to the document model’s structure.

Developers using document databases with ACID support should consider trade-offs between consistency and performance. For example, enabling strict transactional guarantees in a globally distributed database might increase latency due to coordination between nodes. To optimize, limit transactions to critical operations and avoid unnecessary locks. Testing under load is essential, as transactions can strain resources like memory or connection pools. Additionally, not all document databases support the same ACID levels—some may offer “session consistency” rather than strict serializability. Understanding these nuances ensures developers balance reliability with scalability, leveraging ACID where it matters most (e.g., financial systems) while relying on eventual consistency for less critical data.