I’m running a CockroachDB cluster that experiences a high volume of concurrent transactions, and I want to optimize performance. What mechanisms does CockroachDB use to handle contention, and what configuration or indexing strategies can help reduce transaction conflicts and improve throughput?

I’m running a CockroachDB cluster that experiences a high volume of concurrent transactions, and I want to optimize performance. What mechanisms does CockroachDB use to handle contention, and what configuration or indexing strategies can help reduce transaction conflicts and improve throughput?

• database
• cockroachdb

1 Answer 1

CockroachDB handles high concurrency through optimistic concurrency control (OCC) and multi-version concurrency control (MVCC), which allows multiple transactions to proceed without locking resources prematurely. Conflicts are detected during transaction commits based on timestamp ordering, and CockroachDB automatically retries conflicting transactions to maintain serializable isolation. These built-in mechanisms help mitigate contention, but heavy concurrent writes to the same data can still cause conflicts and performance degradation.

To further reduce transaction contention and improve throughput, you can optimize your schema and indexing strategies. Using UUIDs rather than sequential IDs as primary keys prevents data hotspots and evenly distributes writes. Additionally, keeping transactions short, batching operations, and explicitly handling transaction retries in the application layer can greatly enhance performance. Strategic partitioning, hash-sharded indexes, and adjusting key CockroachDB configuration parameters can also help spread workload evenly across your cluster, minimizing contention.