Solr vs Sonic Server vs Sphinx

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Solr

780
644
+ 1
126
Sonic Server

4
24
+ 1
0
Sphinx

906
300
+ 1
32
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Pros of Solr
Pros of Sonic Server
Pros of Sphinx
  • 35
    Powerful
  • 22
    Indexing and searching
  • 20
    Scalable
  • 19
    Customizable
  • 13
    Enterprise Ready
  • 5
    Restful
  • 5
    Apache Software Foundation
  • 4
    Great Search engine
  • 2
    Security built-in
  • 1
    Easy Operating
    Be the first to leave a pro
    • 16
      Fast
    • 9
      Simple deployment
    • 6
      Open source
    • 1
      Lots of extentions

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    What is Solr?

    Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

    What is Sonic Server?

    A fast, lightweight and schema-less search backend. It ingests search texts and identifier tuples that can then be queried against in microseconds.

    What is Sphinx?

    It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.

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    What companies use Solr?
    What companies use Sonic Server?
    What companies use Sphinx?

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    What tools integrate with Solr?
    What tools integrate with Sonic Server?
    What tools integrate with Sphinx?

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    What are some alternatives to Solr, Sonic Server, and Sphinx?
    Lucene
    Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
    Algolia
    Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.
    Elasticsearch
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    See all alternatives