CockroachDB: Distributed SQL Database for Global Apps (2026)
CockroachDB: Distributed SQL Database for Global Apps
Quick Answer
CockroachDB is a distributed SQL database that delivers PostgreSQL compatibility with automatic sharding, serializable isolation, and 99.999% availability. It combines the relational model of traditional databases with the horizontal scalability of NoSQL systems, making it ideal for global, mission-critical applications requiring strong consistency.
What is CockroachDB?
CockroachDB is architected as a “nearly impossible to kill” database system. Unlike legacy databases that rely on active-passive failover, every node in a CockroachDB cluster is identical and capable of serving both read and write traffic, eliminating single points of failure.
Core Philosophy
The name reflects the database’s resilience design: like its biological namesake, CockroachDB is built to survive catastrophic failures through:
- Symmetric, shared-nothing architecture: All nodes are identical
- CAP theorem alignment: Prioritizes Consistency and Partition Tolerance
- Automatic sharding: Data distributed across ranges (512 MiB chunks)
- Raft consensus: Quorum-based replication for durability
Distributed SQL Architecture
Layer 1 - SQL Layer:
- Speaks PostgreSQL wire protocol for broad compatibility
- Parses, plans, and optimizes queries with data locality awareness
- Transforms logical SQL into distributed physical operations
Layer 2 - Transaction Layer:
- SERIALIZABLE isolation by default (strictest SQL standard)
- Multi-Version Concurrency Control (MVCC) without read locks
- Hybrid Logical Clocks for timestamp synchronization
Layer 3 - Distribution Layer:
- Data divided into 512 MiB ranges with 3x replication default
- Raft consensus for each range (quorum of 2/3 must acknowledge writes)
- Automatic reparenting on node failure (seconds to recover)
Key Features
Vector Search & AI Integration
CockroachDB v25+ includes native vector search capabilities:
C-SPANN Architecture:
- Clustered-SPANN algorithm for distributed vector indexing
- RaBitQ quantization (94% compression)
- Transactional vector updates (immediate consistency)
pgvector Compatibility:
- VECTOR(n) data type (up to 16,383 dimensions)
- Standard operators:
<->(Euclidean),<=>(Cosine),<#>(Inner Product) - Hybrid search combining semantic and metadata filtering
High Availability & Resilience
| Feature | Description |
|---|---|
| Automated Replication | 3x default replication factor |
| Rack/Zone Awareness | Control placement of replica ranges |
| Changefeeds | Change Data Capture (CDC) via logical replication |
| Online Upgrades | Zero-downtime schema migrations |
Scalability
- Horizontal sharding: Automatic range-based distribution
- Geo-partitioning: Locate data close to users
- Survival goals: Declarative multi-region configuration
- Elastic scaling: Add nodes without downtime
CockroachDB vs Competitors
CockroachDB vs PostgreSQL
| Feature | CockroachDB | PostgreSQL |
|---|---|---|
| Scaling | Horizontal (auto-sharding) | Vertical (bigger machine) |
| Resilience | Active-active, no downtime | Active-passive with failover |
| Vector Search | Native C-SPANN (distributed) | pgvector (single-node) |
| Consistency | Serializable by default | Configurable isolation levels |
CockroachDB vs MongoDB
| Feature | CockroachDB | MongoDB |
|---|---|---|
| Data Model | Strict relational schema | Flexible document model |
| Transactions | Distributed ACID (serializable) | Multi-document (eventual consistency) |
| Vector Search | Integrated with SQL joins | Separate vector collection |
| Query Language | SQL with joins | MQL aggregation pipeline |
CockroachDB vs Google Spanner
| Feature | CockroachDB | Google Spanner |
|---|---|---|
| Deployment | Multi-cloud capable | GCP-only |
| Clock Technology | Hybrid Logical Clocks | TrueTime (atomic clocks) |
| Pricing | Consumption & provisioned | Provisioned only |
| Open Source | Self-hostable available | Proprietary |
Version Guide (2026)
CockroachDB uses a bifurcated release strategy:
Regular Releases (LTS):
- v24.3, v25.2, v25.4 - Production-ready with extended support
- Designated for mission-critical self-hosted deployments
- 6-month release cadence with long-term support windows
Innovation Releases:
- v25.3, v26.1 (upcoming) - Cutting-edge features
- Faster release cadence with shorter support lifecycle
- Mandatory for CockroachDB Basic (Serverless) tier
EOL Timeline:
- MySQL 8.0 support ends April 2026
- Upgrade to 8.4 LTS or 9.x Innovation track recommended
Use Cases: Best For
- Global SaaS platforms: Multi-region active-active architecture
- Financial systems: Strong consistency with distributed transactions
- Inventory management: Serializable isolation prevents stock discrepancies
- Identity access management: 99.999% availability for authentication
- RAG applications: Unified transactional and vector data storage
Use Cases: Avoid For
- Simple single-region apps: Overhead unnecessary vs single Postgres instance
- Heavy analytics: Use OLAP warehouses (Snowflake, BigQuery) instead
- Edge computing: Requires full nodes, not suitable for serverless edge
- Legacy MySQL applications: Some features still diverging from MySQL behavior
Pricing Structure (2026)
CockroachDB Basic (Serverless)
| Metric | Free Tier | Paid Usage |
|---|---|---|
| Request Units | 50 million / month | $0.20 per million RU |
| Storage | 10 GiB | $0.50 per GiB/month |
CockroachDB Standard
- Model: Provisioned vCPU
- Cost: ~$0.18 per vCPU/hour
- Features: Daily backups, basic multi-region, elastic storage
CockroachDB Advanced
- Model: Dedicated hardware
- Cost: ~$0.60 per vCPU/hour
- Features: CMEK, PCI/HIPAA compliance, infinite scalability, full multi-region
Development Workflow
Prisma Integration
// Prisma with CockroachDB provider
datasource db {
provider = "cockroachdb"
url = env("DATABASE_URL")
}
generator client {
provider = "prisma-client-js"
}
Drizzle ORM Integration
import { drizzle } from 'drizzle-orm/cockroachdb-native';
import { migrate } from 'drizzle-kit/cockroachdb';
const db = drizzle(connection);
// Drizzle offers ~50ms cold starts vs Prisma's ~300ms
Vector Index Creation
-- Create vector index using C-SPANN
CREATE TABLE documents (
id UUID PRIMARY KEY,
content STRING,
embedding VECTOR(1536)
);
CREATE INDEX ON documents
USING HNSW (embedding)
WITH (metric = 'cosine');
Operational Limits
| Limit | Value |
|---|---|
| Max VECTOR dimensions | 16,383 |
| Transaction size | 16 MiB (soft limit) |
| Max document scan | 32,000 documents per transaction |
| Execution time | ~1 second for queries/mutations (10 min for actions) |
FAQ
Is CockroachDB compatible with PostgreSQL?
Yes, CockroachDB speaks the PostgreSQL wire protocol and supports most SQL syntax. However, some PostgreSQL features and extensions are not yet supported.
Does CockroachDB support vector search?
Yes, v25+ includes native vector search via the C-SPANN algorithm with pgvector-compatible syntax and RaBitQ quantization for efficient storage.
What is the difference between LTS and Innovation releases?
LTS (Long-Term Support) releases are stable and recommended for production. Innovation releases include new features faster but have shorter support lifecycles.
Can I run CockroachDB on Kubernetes?
Yes, CockroachDB provides a Kubernetes Operator for automating complex tasks like rolling upgrades, certificate rotation, and scaling in K8s environments.
How does CockroachDB handle network partitions?
CockroachDB prioritizes consistency (CP). During a partition, the minority partition becomes unavailable for writes, while the majority continues processing.
Related Technologies: PostgreSQL, Neon, PlanetScale, Prisma, Drizzle ORM, MongoDB Atlas