Alternatives to Sphinx logo

Alternatives to Sphinx

Elasticsearch, MkDocs, Jekyll, Centrify, and Lucene are the most popular alternatives and competitors to Sphinx.
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What is Sphinx and what are its top alternatives?

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.
Sphinx is a tool in the Search Engines category of a tech stack.

Top Alternatives to Sphinx

  • Elasticsearch

    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). ...

  • MkDocs

    MkDocs

    It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes. ...

  • Jekyll

    Jekyll

    Think of Jekyll as a file-based CMS, without all the complexity. Jekyll takes your content, renders Markdown and Liquid templates, and spits out a complete, static website ready to be served by Apache, Nginx or another web server. Jekyll is the engine behind GitHub Pages, which you can use to host sites right from your GitHub repositories. ...

  • Centrify

    Centrify

    It is privileged identity management and identity as a service solutions stop the breach by securing access to hybrid enterprises through the power of identity services. ...

  • Lucene

    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. ...

  • Apache Solr

    Apache Solr

    It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down. ...

  • YugabyteDB

    YugabyteDB

    An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner. ...

  • Searchkick

    Searchkick

    Searchkick learns what your users are looking for. As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users. ...

Sphinx alternatives & related posts

Elasticsearch logo

Elasticsearch

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19.9K
1.6K
Open Source, Distributed, RESTful Search Engine
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PROS OF ELASTICSEARCH
  • 321
    Powerful api
  • 311
    Great search engine
  • 231
    Open source
  • 213
    Restful
  • 200
    Near real-time search
  • 96
    Free
  • 83
    Search everything
  • 54
    Easy to get started
  • 45
    Analytics
  • 26
    Distributed
  • 6
    Fast search
  • 5
    More than a search engine
  • 3
    Great docs
  • 3
    Awesome, great tool
  • 3
    Easy to scale
  • 2
    Document Store
  • 2
    Nosql DB
  • 2
    Great piece of software
  • 2
    Great customer support
  • 2
    Intuitive API
  • 2
    Fast
  • 2
    Easy setup
  • 2
    Highly Available
  • 1
    Not stable
  • 1
    Scalability
  • 1
    Open
  • 1
    Reliable
  • 1
    Github
  • 1
    Elaticsearch
  • 1
    Actively developing
  • 1
    Responsive maintainers on GitHub
  • 1
    Ecosystem
  • 1
    Easy to get hot data
  • 1
    Potato
  • 0
    Community
CONS OF ELASTICSEARCH
  • 6
    Resource hungry
  • 6
    Diffecult to get started
  • 5
    Expensive
  • 3
    Hard to keep stable at large scale

related Elasticsearch posts

Tim Abbott

We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

I can't recommend it highly enough.

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Tymoteusz Paul
Devops guy at X20X Development LTD · | 23 upvotes · 4.7M views

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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MkDocs logo

MkDocs

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A static site generator
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PROS OF MKDOCS
  • 2
    Gitlab integration
CONS OF MKDOCS
    Be the first to leave a con

    related MkDocs posts

    Nikolaj Ivancic

    I want to build a documentation tool - functionally equivalent to MkDocs. The initial choice ought to be VuePress - but I know of at least one respectable developer who started with VuePress and switched to Nuxt.js. A rich set of "themes" is a plus and all documents ought to be in Markdown.

    Any opinions?

    See more
    Jekyll logo

    Jekyll

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    Blog-aware, static site generator in Ruby
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    PROS OF JEKYLL
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      Github pages integration
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      Open source
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      It's slick, customisable and hackerish
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      Easy to deploy
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      Straightforward cms for the hacker mindset
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      Gitlab pages integration
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      Best for blogging
    • 2
      Easy to integrate localization
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      Low maintenance
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      Huge plugins ecosystem
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      Authoring freedom and simplicity
    CONS OF JEKYLL
    • 4
      Build time increases exponentially as site grows
    • 2
      Lack of developments lately
    • 1
      Og doesn't work with postings dynamically

    related Jekyll posts

    Dale Ross
    Independent Contractor at Self Employed · | 22 upvotes · 995.6K views

    I've heard that I have the ability to write well, at times. When it flows, it flows. I decided to start blogging in 2013 on Blogger. I started a company and joined BizPark with the Microsoft Azure allotment. I created a WordPress blog and did a migration at some point. A lot happened in the time after that migration but I stopped coding and changed cities during tumultuous times that taught me many lessons concerning mental health and productivity. I eventually graduated from BizSpark and outgrew the credit allotment. That killed the WordPress blog.

    I blogged about writing again on the existing Blogger blog but it didn't feel right. I looked at a few options where I wouldn't have to worry about hosting cost indefinitely and Jekyll stood out with GitHub Pages. The Importer was fairly straightforward for the existing blog posts.

    Todo * Set up redirects for all posts on blogger. The URI format is different so a complete redirect wouldn't work. Although, there may be something in Jekyll that could manage the redirects. I did notice the old URLs were stored in the front matter. I'm working on a command-line Ruby gem for the current plan. * I did find some of the lost WordPress posts on archive.org that I downloaded with the waybackmachinedownloader. I think I might write an importer for that. * I still have a few Disqus comment threads to map

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    Josh Dzielak
    Co-Founder & CTO at Orbit · | 5 upvotes · 262.5K views
    Shared insights
    on
    JekyllJekyllHugoHugo

    Earlier this year, I migrated my personal website (dzello.com) from Jekyll to Hugo. My goal with the migration was to make the development environment as pleasant as possible and to make it really easy to add new types of content. For example, I knew I wanted to add a consulting page and some portfolio-style pages to show off talks I had given and projects I had worked on.

    I had heard about how fast Hugo was, so I tried it out with my content after using a simple migration tool. The results were impressive - the startup and rebuild times were in milliseconds, making the process of iterating on content or design less cumbersome. Then I started to see how I could use Hugo to create new page types and was very impressed by the flexibility of the content model. It took me a few days to really understand where content should go with Hugo, but then I felt very confident that I could create many different types of pages - even multiple blogs if I wanted - using a consistent syntax and with full control of the layouts and the URLs.

    After about 6 months, I've been very happy with the results of the migration. The dev environment is light and fast and I feel at ease adding new pages and sections to the site.

    See more
    Centrify logo

    Centrify

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    Leader in securing enterprise identities against cyberthreats that target today’s hybrid IT environment of cloud, mobile and on-premises
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    PROS OF CENTRIFY
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        related Centrify posts

        Lucene logo

        Lucene

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        A high-performance, full-featured text search engine library written entirely in Java
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            related Lucene posts

            Shared insights
            on
            SolrSolrLuceneLucene
            at

            "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’."

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            Apache Solr logo

            Apache Solr

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            An open source search platform
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                related Apache Solr posts

                YugabyteDB logo

                YugabyteDB

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                High-performance, distributed SQL database built for resilience and scale
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                    Shared insights
                    on
                    ScyllaScyllaYugabyteDBYugabyteDB

                    Hello everyone, I am searching for the appropriate solution for a financial use case. I want to handle user balancing in a distributed way. I did a little research and have found YugabyteDB as a solution that offers distributed ACID. Although, I have also found that Scylla seems great in terms of TPS. So I wonder which solutions fit better, or maybe there is another great option I am not considering.

                    Please guys, what do you think?

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                    Searchkick logo

                    Searchkick

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                    Intelligent search made easy
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                    PROS OF SEARCHKICK
                    • 1
                      Open Source
                    CONS OF SEARCHKICK
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                      related Searchkick posts