Two data groups, active-active
==============================

The two data groups pattern spans two geographically separated data
centers, each running its own independent Raft consensus group for local
high availability (HA). With three or more data nodes per group, each
group can use majority-based commit scopes within its own site.

Both data centers serve local reads and writes simultaneously, with
replication between groups keeping both locations current.

.. figure:: /images/two-data-groups.png
   :width: 70% 
   :alt: Two data groups topology

   Two data groups topology

Diagram legend
--------------

Symbols represent node types, group containers, and connection types.

.. figure:: /images/legend.png
   :width: 70% 
   :alt: Diagram legend showing node types, group containers, and connection types

   Diagram legend showing node types, group containers, and connection
   types

When to use this pattern
------------------------

This pattern suits financial services, healthcare, and any application
requiring geo-replication with zero data loss across two active
locations. Both data centers serve writes simultaneously with conflict
resolution, providing true active-active operation across locations.

The advantages of this pattern include the following:

- Provides true disaster recovery, surviving complete data center (DC)
  failure.

- Runs active-active, with both DCs serving reads and writes for local
  latency.

- Geographic redundancy for compliance requirements.

- With local routing, each DC operates independently for most
  operations.

There are some limitations to keep in mind:

- Conflicts are inevitable with optimistic cross-region consistency
  handling.

- Write latency and zero data loss on DC failure are in tension.
  Stronger commit scopes increase latency.

- Without Raft majority (on DC loss), global allocation sequences
  (galloc) eventually run out of allocated ranges and block.

- Global routing isn’t available. The loss of one DC breaks Raft
  majority for the whole cluster.

The Raft majority and galloc limitations can be addressed by adding a
witness location, as described below.

Adding a witness location
-------------------------

Adding a third location, possibly in cloud, containing a single witness
node resolves the Raft majority and galloc limitations. The witness
participates in Raft consensus but doesn’t store user data. With an
odd-number quorum (seven voters: six data nodes and one witness), the
cluster maintains Raft majority even when one DC is lost, restoring
global routing and preventing galloc sequences from exhausting their
allocated ranges.

A witness location is also required when using just two data nodes per
group without a per-group witness, since that configuration can’t
achieve local HA on its own.

.. figure:: /images/two-data-groups-witness.png
   :width: 70% 
   :alt: Two data groups with witness topology

   Two data groups with witness topology

Recommended commit scopes for this pattern
------------------------------------------

- **Majority protect**: synchronous replication to the majority of the
  nodes within the group. The most commonly recommended scope for
  production use.

- **Quorum Commit**: coordinates the commit decision across all
  participating nodes before any node commits locally, ensuring the
  transaction is durable across both regions before it commits.
  Recommended for workloads requiring strict distributed consistency,
  such as payments and core banking. Use
  ``MAJORITY FOR EACH GROUP IN CLUSTER QUORUM COMMIT ABORT ON (timeout = 6s)``
  , which guarantees that any new write leader has the latest committed
  data acknowledged by the prior leader.

- **CAMO**: when using two data nodes and one witness per group, CAMO
  adds exactly-once transaction guarantees over synchronous replication.

- **Local protect**: asynchronous replication with durability only for
  the local node. Not recommended for production use.

Commit scopes make different trade-offs across performance, durability,
consistency, and scalability.

.. figure:: /images/two-data-group-behavior.png
   :width: 70% 
   :alt: Two data groups behavior diagram

   Two data groups behavior diagram