What is Sphinx and what are its top alternatives?
Top Alternatives to Sphinx
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). ...
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. ...
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. ...
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 Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities. ...
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. ...
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 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
- Powerful api321
- Great search engine311
- Open source230
- Near real-time search199
- Search everything83
- Easy to get started54
- Fast search6
- More than a search engine5
- Great docs3
- Easy to scale3
- Awesome, great tool3
- Document Store2
- Nosql DB2
- Great piece of software2
- Great customer support2
- Intuitive API2
- Easy setup2
- Highly Available2
- Easy to get hot data1
- Actively developing1
- Responsive maintainers on GitHub1
- Not stable1
- Resource hungry6
- Diffecult to get started6
- Hard to keep stable at large scale4
related Elasticsearch posts
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.
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.
- Gitlab integration2
related MkDocs posts
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.
- Github pages integration75
- Open source53
- It's slick, customisable and hackerish37
- Easy to deploy23
- Straightforward cms for the hacker mindset22
- Gitlab pages integration6
- Best for blogging4
- Easy to integrate localization2
- Low maintenance2
- Huge plugins ecosystem1
- Authoring freedom and simplicity1
- Build time increases exponentially as site grows4
- Lack of developments lately2
- Og doesn't work with postings dynamically1
related Jekyll posts
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
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.
related Centrify posts
related Lucene posts
"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’."
related Apache Solr posts
related YugabyteDB posts
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?