Sharding (also known as Data Partitioning) is the process of splitting a large dataset into many small partitions which are placed on different machines. Each partition is known as a “shard”.
Each shard has …
Read MoreDistributed systems will face network partitioning at some point in their life cycle. When network partitioning happens, CAP theorem dictates that if you pick availability, you cannot have true(strong) consistency, but you can still provide “eventual …
Read MoreLoad balancing is one of the founding pillars of designing distributed systems. A load balancer simply distributes a set of requested operations (database write requests, cache queries) effectively across a set of servers.
Here’s an example …
Read MoreCAP Theorem has become the holy grail of distributed system design in recent years. CAP theorem states that any distributed computer system can support only any two among consistency, availability, and partition tolerance.
Let’s explore the …
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Consistent hashing is one of the techniques used to bake in scalability into the storage architecture of your system from grounds up.
In a distributed system, consistent hashing helps in solving the following scenarios:
For many C++ developers, API Design probably makes number 3 or 4 on their priority list. Majority of developers flock to C++ for the raw power and control it provides. Consequently, performance and optimization is what occupies the thoughts of …
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