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doc: replace Scylla with ScyllaDB on the Fault Tolerance page

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Anna Stuchlik
2022-08-11 16:14:33 +02:00
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docs/architecture/architecture-fault-tolerance.rst
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@@ -1,7 +1,7 @@
Scylla Architecture - Fault Tolerance
=====================================
ScyllaDB Architecture - Fault Tolerance
========================================
Scylla replicates data according to a :term:`replication<Replication>` strategy that you choose. This strategy will determine the placement of the replicated data. Scylla runs nodes in a hash ring. All nodes are equal: there are no master, slave, or replica sets.
ScyllaDB replicates data according to a :term:`replication<Replication>` strategy that you choose. This strategy will determine the placement of the replicated data. ScyllaDB runs nodes in a hash ring. All nodes are equal: there are no master, slave, or replica sets.
The :term:`Replication Factor (RF)<Replication Factor (RF)>` is equivalent to the number of nodes where data (rows and partitions) are replicated. Data is replicated to multiple (RF=N) nodes.
@@ -55,19 +55,19 @@ The Consistency Level itself impacts availability. A **higher** Consistency Leve
Refer to the :ref:`Consistency Level table <consistency-levels-reference>` to get information about the Consistency Levels that are available for a read or write operation.
Scylla, as do many distributed database systems, adheres to the :term:`CAP Theorem<CAP Theorem>`. The **CAP Theorem** is the notion that **Consistency**, **Availability** and **Partition Tolerance** of data are mutually dependent in a distributed system. Increasing any 2 of these factors will reduce the third.
ScyllaDB, as do many distributed database systems, adheres to the :term:`CAP Theorem<CAP Theorem>`. The **CAP Theorem** is the notion that **Consistency**, **Availability** and **Partition Tolerance** of data are mutually dependent in a distributed system. Increasing any 2 of these factors will reduce the third.
Scylla adheres to the CAP theorem in the following way:
ScyllaDB adheres to the CAP theorem in the following way:
.. image:: 6-CAP_Theorem.jpg
Scylla chooses availability and partition tolerance over consistency, such that:
ScyllaDB chooses availability and partition tolerance over consistency, such that:
- It’s impossible to be both consistent and highly available during a network partition;
- If we sacrifice consistency, we can be highly available.
You’ll need to design your application around Scylla’s data modeling, but the net result is an application that will never go down.
You’ll need to design your application around ScyllaDB’s data modeling, but the net result is an application that will never go down.
Additional Resources
@@ -75,4 +75,4 @@ Additional Resources
* :doc:`Consistency Level Console Demo </architecture/console-CL-full-demo>`
* :doc:`Consistency Levels </cql/consistency/>`
* From Scylla Univeristy: take the `Consistency Level lesson <https://university.scylladb.com/courses/scylla-essentials-overview/lessons/architecture/topic/consistency-level-cl/>`_
* From ScyllaDB Univeristy: take the `Consistency Level lesson <https://university.scylladb.com/courses/scylla-essentials-overview/lessons/architecture/topic/consistency-level-cl/>`_