Bonsai聽vs聽Elasticsearch聽vs聽Searchify

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Bonsai
Bonsai

15
14
+ 1
0
Elasticsearch
Elasticsearch

9.3K
6.3K
+ 1
1.6K
Searchify
Searchify

1
4
+ 1
1
- No public GitHub repository available -
- No public GitHub repository available -

What is Bonsai?

Your customers expect fast, near-magical results from your search. Help them find what they鈥檙e looking for with Bonsai Elasticsearch. Our fully managed Elasticsearch solution makes it easy to create, manage, and test your app's search.

What is 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).

What is Searchify?

Easily add custom full-text search, without the cost or complexity of managing search servers
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Why do developers choose Bonsai?
Why do developers choose Elasticsearch?
Why do developers choose Searchify?
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        What companies use Bonsai?
        What companies use Elasticsearch?
        What companies use Searchify?

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        What tools integrate with Bonsai?
        What tools integrate with Elasticsearch?
        What tools integrate with Searchify?

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        What are some alternatives to Bonsai, Elasticsearch, and Searchify?
        QuickBooks
        It is an accounting software package. You can access and manage your books from your computer, laptop, tablet, or smartphone anytime you choose. Create access privileges so that your colleague or accountant can login and work.
        Freshbooks
        It is simple and intuitive. It makes running your small business easy, fast and secure. Easily send invoices, track time, manage expenses, and get paid online.
        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.
        Amazon Elasticsearch Service
        Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.
        Swiftype
        Swiftype is the easiest way to add great search to your website or mobile application.
        See all alternatives
        Decisions about Bonsai, Elasticsearch, and Searchify
        Tim Specht
        Tim Specht
        鈥嶤o-Founder and CTO at Dubsmash | 16 upvotes 94.4K views
        atDubsmashDubsmash
        Elasticsearch
        Elasticsearch
        Algolia
        Algolia
        Memcached
        Memcached
        #SearchAsAService

        Although we were using Elasticsearch in the beginning to power our in-app search, we moved this part of our processing over to Algolia a couple of months ago; this has proven to be a fantastic choice, letting us build search-related features with more confidence and speed.

        Elasticsearch is only used for searching in internal tooling nowadays; hosting and running it reliably has been a task that took up too much time for us in the past and fine-tuning the results to reach a great user-experience was also never an easy task for us. With Algolia we can flexibly change ranking methods on the fly and can instead focus our time on fine-tuning the experience within our app.

        Memcached is used in front of most of the API endpoints to cache responses in order to speed up response times and reduce server-costs on our side.

        #SearchAsAService

        See more
        Julien DeFrance
        Julien DeFrance
        Principal Software Engineer at Tophatter | 16 upvotes 487.1K views
        atSmartZipSmartZip
        Rails
        Rails
        Rails API
        Rails API
        AWS Elastic Beanstalk
        AWS Elastic Beanstalk
        Capistrano
        Capistrano
        Docker
        Docker
        Amazon S3
        Amazon S3
        Amazon RDS
        Amazon RDS
        MySQL
        MySQL
        Amazon RDS for Aurora
        Amazon RDS for Aurora
        Amazon ElastiCache
        Amazon ElastiCache
        Memcached
        Memcached
        Amazon CloudFront
        Amazon CloudFront
        Segment
        Segment
        Zapier
        Zapier
        Amazon Redshift
        Amazon Redshift
        Amazon Quicksight
        Amazon Quicksight
        Superset
        Superset
        Elasticsearch
        Elasticsearch
        Amazon Elasticsearch Service
        Amazon Elasticsearch Service
        New Relic
        New Relic
        AWS Lambda
        AWS Lambda
        Node.js
        Node.js
        Ruby
        Ruby
        Amazon DynamoDB
        Amazon DynamoDB
        Algolia
        Algolia

        Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

        I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

        For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

        Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

        Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

        Future improvements / technology decisions included:

        Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

        As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

        One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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        Interest over time
        Reviews of Bonsai, Elasticsearch, and Searchify
        Review ofBonsaiBonsai

        We used Bonsai happily for 2 years, great service, but then they forced us to upgrade or we'd have to pay 5x the price! VERY unhappy about that. caused us days of unnecessary work.

        How developers use Bonsai, Elasticsearch, and Searchify
        Avatar of imgur
        imgur uses ElasticsearchElasticsearch

        Elasticsearch is the engine that powers search on the site. From a high level perspective, it鈥檚 a Lucene wrapper that exposes Lucene鈥檚 features via a RESTful API. It handles the distribution of data and simplifies scaling, among other things.

        Given that we are on AWS, we use an AWS cloud plugin for Elasticsearch that makes it easy to work in the cloud. It allows us to add nodes without much hassle. It will take care of figuring out if a new node has joined the cluster, and, if so, Elasticsearch will proceed to move data to that new node. It works the same way when a node goes down. It will remove that node based on the AWS cluster configuration.

        Avatar of Instacart
        Instacart uses ElasticsearchElasticsearch

        The very first version of the search was just a Postgres database query. It wasn鈥檛 terribly efficient, and then at some point, we moved over to ElasticSearch, and then since then, Andrew just did a lot of work with it, so ElasticSearch is amazing, but out of the box, it doesn鈥檛 come configured with all the nice things that are there, but you spend a lot of time figuring out how to put it all together to add stemming, auto suggestions, all kinds of different things, like even spelling adjustments and tomato/tomatoes, that would return different results, so Andrew did a ton of work to make it really, really nice and build a very simple Ruby gem called SearchKick.

        Avatar of AngeloR
        AngeloR uses ElasticsearchElasticsearch

        We use ElasticSearch for

        • Session Logs
        • Analytics
        • Leaderboards

        We originally self managed the ElasticSearch clusters, but due to our small ops team size we opt to move things to managed AWS services where possible.

        The managed servers, however, do not allow us to manage our own backups and a restore actually requires us to open a support ticket with them. We ended up setting up our own nightly backup since we do per day indexes for the logs/analytics.

        Avatar of Brandon Adams
        Brandon Adams uses ElasticsearchElasticsearch

        Elasticsearch has good tooling and supports a large api that makes it ideal for denormalizing data. It has a simple to use aggregations api that tends to encompass most of what I need a BI tool to do, especially in the early going (when paired with Kibana). It's also handy when you just want to search some text.

        Avatar of Ana Phi Sancho
        Ana Phi Sancho uses ElasticsearchElasticsearch

        Self taught : acquired knowledge or skill on one's own initiative. Open Source Search & Analytics. -time search and analytics engine. Search engine based on Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

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