# ACID vs BASE and CAP Theorem
# ACID properties in DBMS
- Atomicity: This property ensures that either all the operations of a transaction reflect in database or none. A=400 and B=700 / some transfer / cumulative always 1100 even if failed
- Consistency: To preserve the consistency of database, the execution of transaction should take place in isolation (that means no other transaction should run concurrently when there is a transaction already running). A=400 / 100 trasaction to B & C / two transaction seperately for reading the value A 1st transaction A=400 then 2nd transacation A=300
- Isolation: For every pair of transactions, one transaction should start execution only when the other finished execution.
- Durability : Once a transaction completes successfully, the changes it has made into the database should be permanent even if there is a system failure.
# BASE:
An alternative to ACID is BASE
- Basically Available: The system is guaranteed to be available for querying by all users. (No isolation here.)
- Soft State: The values stored in the system may change because of the eventual consistency model, as described in the next bullet.
- Eventually Consistent: As data is added to the system, the system’s state is gradually replicated across all nodes.
# CAP Theorem
- Consistency: Similar to the C in ACID, all nodes in the system would have the same view of the data at any time.
- Availability: The system always responds to requests.
- Partition tolerance: The system remains online if network problems occur between system nodes.
Eric Brewer’s CAP theorem says that if you want consistency, availability, and partition tolerance, you have to settle for two out of three. (For a distributed system, partition tolerance means the system will continue to work unless there is a total network failure. A few nodes can fail and the system keeps going.)