Consistency
Consistency, in the context of databases, refers to the principle that ensures data remains accurate and reliable over time.
This principle is applied when multiple copies of data are stored on different hardware. Such a database is referred to as replicated.
Replicated databases are widely utilized by companies whose products are used globally.
Instead of relying on a single server in one location, they employ numerous servers spread across the world to ensure similar accessibility for users from different countries.
Consistency plays a vital role in replicated databases, ensuring that all copies or replicas of data within the system maintain uniformity over time.
This means that regardless of which replica a user accesses, they will see the same up-to-date data, providing a cohesive and reliable experience across the entire system.
Types of consistency
- Strong Consistency: Ensures all replicas have the same up-to-date data at all times. Updates are synchronized across replicas immediately, guaranteeing the highest level of consistency. However, this synchronous replication can lead to increased latency and reduced availability;
- Eventual Consistency: Prioritizes availability over immediate consistency. Replicas may temporarily differ after updates but eventually converge to a consistent state in some short period of time. Updates are asynchronously propagated, allowing local processing without waiting for synchronization;
- Week consistency: There's no guarantee that all nodes in a distributed system will see the same data. Updates to the system might not be instantly propagated to all nodes, leading to the possibility of different nodes observing different versions of the data for a long period of time.
Imagine a social media platform where posts and comments are stored in replicated databases across various locations.
Now, due to the way these databases are set up, sometimes updates can take a bit of time to spread everywhere.
For example, if someone deletes a popular post on one replica of the platform while someone else adds a comment on another replica, it might take a while for that post to disappear from all places. So, users could end up seeing deleted posts with new comments, which can be confusing and make things inconsistent for them.
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Course Content
Advanced Techniques in SQL
Advanced Techniques in SQL
Consistency
Consistency, in the context of databases, refers to the principle that ensures data remains accurate and reliable over time.
This principle is applied when multiple copies of data are stored on different hardware. Such a database is referred to as replicated.
Replicated databases are widely utilized by companies whose products are used globally.
Instead of relying on a single server in one location, they employ numerous servers spread across the world to ensure similar accessibility for users from different countries.
Consistency plays a vital role in replicated databases, ensuring that all copies or replicas of data within the system maintain uniformity over time.
This means that regardless of which replica a user accesses, they will see the same up-to-date data, providing a cohesive and reliable experience across the entire system.
Types of consistency
- Strong Consistency: Ensures all replicas have the same up-to-date data at all times. Updates are synchronized across replicas immediately, guaranteeing the highest level of consistency. However, this synchronous replication can lead to increased latency and reduced availability;
- Eventual Consistency: Prioritizes availability over immediate consistency. Replicas may temporarily differ after updates but eventually converge to a consistent state in some short period of time. Updates are asynchronously propagated, allowing local processing without waiting for synchronization;
- Week consistency: There's no guarantee that all nodes in a distributed system will see the same data. Updates to the system might not be instantly propagated to all nodes, leading to the possibility of different nodes observing different versions of the data for a long period of time.
Imagine a social media platform where posts and comments are stored in replicated databases across various locations.
Now, due to the way these databases are set up, sometimes updates can take a bit of time to spread everywhere.
For example, if someone deletes a popular post on one replica of the platform while someone else adds a comment on another replica, it might take a while for that post to disappear from all places. So, users could end up seeing deleted posts with new comments, which can be confusing and make things inconsistent for them.
Everything was clear?
