Gatling vs Solr: What are the differences?
Developers describe Gatling as "open-source load testing framework based on Scala, Akka and Netty". Gatling is a highly capable load testing tool. It is designed for ease of use, maintainability and high performance Out of the box, Gatling comes with excellent support of the HTTP protocol that makes it a tool of choice for load testing any HTTP server. As the core engine is actually protocol agnostic, it is perfectly possible to implement support for other protocols. For example, Gatling currently also ships JMS support.. On the other hand, Solr is detailed as "An open source enterprise search server based on Lucene search library, with XML/HTTP and JSON APIs, hit highlighting, faceted search, caching, replication etc". 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.
Gatling belongs to "Load and Performance Testing" category of the tech stack, while Solr can be primarily classified under "Search Engines".
Gatling is an open source tool with 4.3K GitHub stars and 918 GitHub forks. Here's a link to Gatling's open source repository on GitHub.
Slack, Coursera, and Zalando are some of the popular companies that use Solr, whereas Gatling is used by Streamdata.io, SpectoLabs Ltd, and StellaService. Solr has a broader approval, being mentioned in 140 company stacks & 42 developers stacks; compared to Gatling, which is listed in 21 company stacks and 14 developer stacks.
What is Gatling?
What is Solr?
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"Slack provides two strategies for searching: Recent and Relevant. Recent search finds the messages that match all terms and presents them in reverse chronological order. If a user is trying to recall something that just happened, Recent is a useful presentation of the results.
Relevant search relaxes the age constraint and takes into account the Lucene score of the document — how well it matches the query terms (Solr powers search at Slack). Used about 17% of the time, Relevant search performed slightly worse than Recent according to the search quality metrics we measured: the number of clicks per search and the click-through rate of the search results in the top several positions. We recognized that Relevant search could benefit from using the user’s interaction history with channels and other users — their ‘work graph’."
elastic search 와 함께 유명한 검색 엔진 오픈 소스 중 하나 이다. 처음 설정할 것이 많은데, 어플리케이션의 이해가 없다면 잦은 수정이 필요하다. Solr Client 로 제어 할 수 없고 Server 에서 설정해 줘야하는 것들이 있어 서버 설정하는 부분이 중요하다. 서버 설정만 잘 되있다면, Client 쪽 소스는 별게 없다.
중요한 건 형태소 분석기....
Full text search is provided by a SOLR cluster. This is done on Master/Slave replication with Varnish as a cache.