Sharding in ArangoDB is a technique used to horizontally partition data across multiple servers, known as shards, to distribute the workload and storage capacity of the database. This horizontal scaling approach allows ArangoDB to handle large volumes of data and high throughput by spreading the data across multiple nodes in a cluster.
Here's how sharding works in ArangoDB :Partitioning Data :
* Sharding divides the dataset into smaller subsets, called shards or partitions, based on a shard key.
* The shard key is a document attribute or a combination of attributes that determines the placement of documents into shards.
* ArangoDB automatically routes queries to the appropriate shard based on the shard key, ensuring that related data is stored together on the same shard.
Distributing Shards :
* Shards are distributed across multiple servers in a cluster to evenly distribute the data and workload.
* ArangoDB uses a distributed consensus algorithm, such as Raft or Paxos, to manage shard distribution and ensure data consistency and fault tolerance.
Scalability :
* Sharding allows ArangoDB to scale horizontally by adding more servers to the cluster as the dataset grows or the workload increases.
* Each new server added to the cluster can host additional shards, increasing the storage capacity and processing power of the database.
Performance :
* Sharding improves query performance by distributing query processing across multiple shards, allowing parallel execution of queries.
* Additionally, sharding reduces the size of individual shards, resulting in faster query execution times and lower latency.
Fault Tolerance :
* Sharding enhances fault tolerance by replicating shards across multiple servers in the cluster.
* In the event of a server failure, ArangoDB can automatically fail over to the replica shard on another server, ensuring data availability and reliability.
Configuring Sharding :
* In ArangoDB, sharding is configured at the collection level using the shardKeys parameter when creating or modifying a collection.
* Developers can specify one or more shard keys to partition the data based on specific criteria, such as user ID, timestamp, or geographic location.
