sphinxsearchHow do SphinxSearch and ElasticSearch compare in terms of performance and scalability?

SphinxSearch and ElasticSearch are two popular open-source search engine solutions. Both provide high-performance and scalability, but they differ in how they achieve these goals.

SphinxSearch's approach to performance and scalability is primarily based on data partitioning. It stores data in multiple indexes and distributes queries across those multiple indexes. This allows for greater scalability and faster query response times. For example, the following code block creates two indexes and distributes queries across them:

index my_index_1
{
    source = my_source_1
    path = /var/data/my_index_1
}

index my_index_2
{
    source = my_source_2
    path = /var/data/my_index_2
}

searchd
{
    listen = 9312
    log = /var/log/searchd.log
    query_log = /var/log/query.log
    binlog_path = /var/data/
}

ElasticSearch, on the other hand, takes a distributed approach to performance and scalability. It uses a cluster of nodes to store data and distribute queries across them. This allows for increased scalability and faster query response times. For example, the following code block creates a cluster of two nodes and distributes queries across them:

cluster.name: my_cluster
node.name: node-1
node.master: true
node.data: true

cluster.name: my_cluster
node.name: node-2
node.master: false
node.data: true

In summary, SphinxSearch and ElasticSearch both provide high-performance and scalability, but they use different approaches to achieve these goals. SphinxSearch uses data partitioning while ElasticSearch uses a distributed cluster of nodes.

Code explanation

• index my_index_1: creates an index for data storage
• path = /var/data/my_index_1: specifies the path where the index will be stored
• listen = 9312: specifies the port the search engine will listen to
• log = /var/log/searchd.log: specifies the log file for search engine
• query_log = /var/log/query.log: specifies the log file for queries
• binlog_path = /var/data/: specifies the path for binary logs
• cluster.name: my_cluster: creates a cluster with the specified name
• node.name: node-1: specifies the name of the node
• node.master: true: specifies that the node is a master node
• node.data: true: specifies that the node is a data node

• Helpful links

  • https://sphinxsearch.com/
  • https://www.elastic.co/

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