What Is MVCC (Multiversion Concurrency Control)?
MVCC (multiversion concurrency control) is a concurrency control mechanism used in databases and distributed data systems to allow multiple transactions to read and write data simultaneously without blocking each other. It works by maintaining multiple versions of the same data so each transaction can operate on a consistent snapshot.
MVCC is a foundational technique for high-performance systems that must balance data consistency, availability, and concurrency under heavy load.
MVCC Explained
In traditional lock-based systems, read and write operations often block one another, limiting throughput as concurrency increases. MVCC avoids this by separating readers from writers using versioned data rather than exclusive locks.
Instead of overwriting data in place, updates create new versions. Readers continue to access the version that was valid when their transaction began, while writers proceed independently. This model is especially effective in distributed systems and in-memory architectures, where coordinating locks across nodes introduces latency.
MVCC is widely used in relational databases, distributed databases, and in-memory computing platforms where concurrent access is the norm.
How MVCC Works
MVCC relies on snapshots and versioned records rather than pessimistic locking.
A typical MVCC workflow looks like this:
Transaction starts
Each transaction is assigned a logical timestamp or transaction ID.
Snapshot is established
The transaction sees a consistent view of the data as it existed at that moment.
Writes create new versions
Updates generate new record versions instead of modifying existing ones.
Commit validation occurs
The system checks for write conflicts based on the isolation level and MVCC implementation.
Old versions are cleaned up
Once no active transaction requires them, obsolete versions are reclaimed through background cleanup.
Key Characteristics of MVCC
Non-Blocking Concurrency
Readers do not block writers, and writers do not block readers, enabling high parallelism in transactional workloads.
Snapshot Isolation
Each transaction operates on a stable, isolated snapshot of the data, preventing dirty reads and inconsistent query results.
Versioned Data Storage
Multiple versions of records coexist temporarily, enabling concurrent access without contention.
Scalability at High Load
By minimizing lock coordination, MVCC systems scale more effectively as transaction volume grows.
Background Cleanup Required
Old data versions must be removed through garbage collection to prevent storage bloat.
MVCC in Popular Databases and Systems
MVCC is widely adopted across modern database engines, though implementations vary:
PostgreSQL
Uses MVCC as a core design principle, storing multiple row versions and relying on vacuum processes to clean up obsolete data.
MySQL (InnoDB)
Implements MVCC using undo logs, allowing consistent reads without locking while managing version visibility internally.
Oracle Database
Uses undo segments to provide read consistency, enabling snapshot-based reads similar to MVCC.
SQL Server
Supports row versioning–based isolation levels, which use MVCC concepts to reduce blocking in concurrent workloads.
Common Use Cases for MVCC
- High-concurrency transactional systems
- Real-time analytics on live operational data
- Distributed databases and data grids
- Microservices sharing mutable state
- Financial, e-commerce, and event-driven platforms
How MVCC Is Used in GridGain
GridGain applies MVCC principles within its distributed, in-memory architecture built on Apache Ignite to support ACID transactions at scale.
In clustered environments, coordinating locks across nodes can significantly increase latency. MVCC reduces this overhead by allowing transactions to read consistent snapshots while writes proceed independently.
Within GridGain, MVCC is closely related to:
Distributed ACID transactions
Ensuring consistency across nodes without heavy locking
In-memory data grid architecture
Minimizing coordination costs in partitioned, in-memory storage
Distributed SQL queries
Supporting consistent query results under concurrent writes
Fault-tolerant system design
Combining versioned data with replication and persistence
This allows GridGain to operate not just as a cache, but as a transactional and analytical data platform suitable for mission-critical systems.
MVCC vs Traditional Lock-Based Concurrency Control
Operational complexity Requires version cleanup Requires deadlock handling
| Aspect | MVCC | Lock-Based Concurrency |
|---|---|---|
| Read/write interaction | Readers and writers do not block each other | Reads and writes block |
| Throughput | High under concurrent load | Degrades as contention increases |
| Latency | Predictable | Can spike under load |
| Storage overhead | Higher due to multiple versions | Lower |
Frequently Asked Questions
No. Snapshot isolation is a consistency model, while MVCC is the mechanism used to implement it.
No. MVCC significantly reduces read-write contention, but some locking is still required for writes, commits, and metadata management.
Yes. Because multiple versions of data are stored temporarily, MVCC systems require additional memory or disk space and background cleanup processes.
MVCC is best suited for systems with many concurrent reads and writes, long-running queries, or requirements for low latency and high availability.