How do you ensure consistency in a distributed database?

1 Answer

1. First is to take the lock before writing anything to the database or caching system. This ensures read and write lock. This includes master server as well.
2. Secondly, if replication fails then there is the added complex layer of rollovers. This ensures that data is consistent if not then it is not applied.

How can I make my consistency strong?

To have strong consistency, developers must compromise on the scalability and performance of their application. Simply put, data has to be locked during the period of update or replication process to ensure that no other processes are updating the same data.

What is database strong consistency?

Strong Consistency simply means the data must be strongly consistent at all times. All the server nodes across the world should contain the same value as an entity at any point in time. And the only way to implement this behavior is by locking down the nodes when being updated.

What makes a database scalable?

What Makes a Scalable Database? Database scalability is a concept in analytics database design that emphasizes the capability of a database to handle growth in the amount of data and users. In the modern applications sphere, two types of workloads have emerged – namely analytical and transactional workloads.

What is strong consistency model?

Strong consistency is one of the consistency models used in the domain of concurrent programming (e.g., in distributed shared memory, distributed transactions). The protocol is said to support strong consistency if: All accesses are seen by all parallel processes (or nodes, processors, etc.)

What is consistency in a database?

Consistency. Consistency in database systems refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules.

Where is strong consistency used?

What does consistency mean in databases?

Consistency in database systems refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules.

How do you make a database scalable?

Horizontal Scaling

1. Adding read replicas to handle Read-Heavy workloads.
2. Reading from the cache before hitting the primary DB to reduce database load.
3. Sharding your database into multiple servers to improve both read and write performance.

Why is consistency important in a database?

Database consistency is important because it regulates the data that is coming in and rejects the data that doesn’t fit into the rules. Consistency rules are often enforced through constraints at a field level. A constraint specifies a rule governing a given record or field-level value.

What is scalability in database design?

Database scalability is a concept in database design that emphasizes on the capability of a database to handle growth in the amount of data and users.

How to improve the performance of a relational database system?

Each relational database system provides a set of parameters that can be tweaked to improve performance. Therefore it is advisable to check parameters that are used in the specific database system. Schema design offers the biggest opportunity for a system developer to make decisions that will affect the scalability and performance of a database.

What factors affect the capacity of a database to scale?

At the database level configuration, schema design, indexing, and query design affect the capability of a database to scale. Each relational database system provides a set of parameters that can be tweaked to improve performance.

How do scalability and elasticity help to improve availability and performance?

So how do scalability and elasticity help to improve availability and performance? Scalability refers to the capability of a system to handle a growing amount of work, or its potential to perform more total work in the same elapsed time when processing power is expanded to accommodate growth.