diff --git a/pages/clustering/high-availability.mdx b/pages/clustering/high-availability.mdx
index 998378e05..828cc281a 100644
--- a/pages/clustering/high-availability.mdx
+++ b/pages/clustering/high-availability.mdx
@@ -54,4 +54,11 @@ deployment.
A complete reference of all commands for managing coordinators, registering
instances, and operating the cluster.
+### [Reference architectures](/clustering/high-availability/reference-architectures)
+Explore validated HA deployment topologies, including minimal setups,
+production-ready clusters, scaling patterns, cross–data center deployments, and
+advanced architectures for low-latency or geographically distributed
+environments.
+
+
diff --git a/pages/clustering/high-availability/_meta.ts b/pages/clustering/high-availability/_meta.ts
index daa1d1d68..1c68776b4 100644
--- a/pages/clustering/high-availability/_meta.ts
+++ b/pages/clustering/high-availability/_meta.ts
@@ -6,4 +6,5 @@ export default {
"setup-ha-cluster-k8s": "Set up HA cluster with K8s",
"best-practices": "Best practices",
"ha-commands-reference": "Reference commands",
+ "ha-reference-architectures": "Reference architectures",
}
diff --git a/pages/clustering/high-availability/ha-reference-architectures.mdx b/pages/clustering/high-availability/ha-reference-architectures.mdx
new file mode 100644
index 000000000..c1580d77a
--- /dev/null
+++ b/pages/clustering/high-availability/ha-reference-architectures.mdx
@@ -0,0 +1,152 @@
+---
+title: Reference architectures
+description: Explore different high availability cluster configurations and deployment scenarios for Memgraph.
+---
+
+import { CommunityLinks } from '/components/social-card/CommunityLinks'
+
+# Reference architectures
+
+This page presents different deployment scenarios for Memgraph HA clusters,
+covering various aspects such as the number of data centers, geographic
+distribution, performance scaling, consistency requirements, and fault tolerance
+considerations.
+
+## Basic architectures
+
+### Typical HA cluster
+
+A typical HA deployment consists of:
+
+- **Three data instances** (1 MAIN + 2 REPLICAs)
+- **Three coordinators** (1 Leader + 2 Followers)
+
+Data instances require hardware sized for memory-intensive workloads.
+Coordinators, responsible for cluster state and failover logic, are lightweight
+and typically run comfortably on **4-8 GB RAM servers**.
+
+
+
+
+### Minimal HA cluster
+
+The smallest valid HA configuration consists of:
+
+- **Two data instances** (1 MAIN + 1 REPLICA)
+- **Three coordinators**
+
+This results in a **minimum of five total instances**.
+
+
+
+
+## Architectures for scaling performance
+
+Memgraph is an in-memory graph database designed for extremely high read and
+write throughput on a single machine. Distributing this architecture across
+multiple servers increases resource requirements but enables scaling for
+demanding real-time analytics and transactional workloads.
+
+> Before scaling horizontally or vertically, first ensure your standalone
+> instance has been fully optimized.
+
+
+### Scaling reads
+
+To increase read capacity, **add additional REPLICA instances**. Replicas can
+serve **read-only workloads**, making them ideal for analytics, reporting, and
+latency-sensitive queries.
+
+
+
+### Scaling writes
+
+Write scalability is achieved by **scaling the MAIN vertically** (more CPU,
+memory). Only the MAIN accepts writes, which aligns with the design of graph
+workloads, especially multi-hop traversals, which do not benefit from horizontal
+write sharding.
+
+Why vertical scaling works well in Memgraph:
+
+- **Fine-grained locking**
+- **Lock-free skiplists** for node/relationship storage
+- **MVCC (Multi-Version Concurrency Control)** ensuring writers do not block
+ readers
+- Predictable scaling under higher CPU core counts
+
+
+
+Horizontal write scaling, often available in non-graph databases, is not
+suitable for graph workloads because multi-hop queries would require cross-shard
+traversal, significantly degrading performance and consistency guarantees.
+
+
+## Architectures for robust fault tolerance
+
+### Cross-data center deployment
+
+For disaster recovery and data center-level fault tolerance, Memgraph HA can be
+deployed across **three separate data centers**, for example:
+
+- **Data Center 1:** MAIN + 1 Coordinator
+- **Data Center 2:** REPLICA + 1 Coordinator
+- **Data Center 3:** Coordinator
+
+**Failure behavior:**
+
+- **Data Center 1 failure**
+ - RAFT retains quorum
+ - REPLICA is automatically promoted to MAIN
+ - Cluster continues serving reads and writes
+
+- **Data Center 2 failure**
+ - MAIN remains available
+ - Coordinators maintain quorum
+ - REPLICA recovers automatically when restored
+
+- **Data Center 3 failure**
+ - Quorum maintained with the remaining two coordinators
+ - No failover needed
+
+
+
+## Other architectures
+
+### Centralized MAIN with remote REPLICAs
+
+Some organizations need **low-latency local reads** across multiple regions
+while keeping writes centralized for consistency.
+
+Deploy remote REPLICAs using **ASYNC** replication in regional data centers:
+
+- Local reads are extremely fast
+- MAIN remains authoritative
+- Writes remain centralized
+
+Set the coordinator setting:
+```
+sync_failover_only = true
+```
+
+This ensures failover **never promotes a remote ASYNC replica**.
+
+
+
+
+### Centralized MAIN with regional REPLICAs + failover protection
+
+To add failover capability to the centralized architecture, add a `SYNC` or
+`STRICT_SYNC` REPLICA in the same region as the MAIN.
+
+This creates:
+
+- **Local failover** between MAIN and the nearby SYNC replica
+- **Remote read replicas** in other regions for latency-sensitive workloads
+
+Only SYNC or STRICT_SYNC replicas are eligible for failover.
+
+
+
+---
+
+
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