Elasticsearch vs Swiftype

Elasticsearch
Elasticsearch

8K
1.6K
2.9K
Swiftype
Swiftype

67
11
21
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Elasticsearch vs Swiftype: What are the differences?

Elasticsearch: Open Source, Distributed, RESTful Search Engine. 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); Swiftype: Powerful and scalable search for any application or website. Swiftype is the easiest way to add great search to your website or mobile application.

Elasticsearch and Swiftype can be categorized as "Search as a Service" tools.

Some of the features offered by Elasticsearch are:

  • Distributed and Highly Available Search Engine.
  • Multi Tenant with Multi Types.
  • Various set of APIs including RESTful

On the other hand, Swiftype provides the following key features:

  • Quick Start- Install by pasting a JavaScript snippet in your page.
  • Autocomplete- our search engines come with autocomplete built-in
  • Detailed Analytics- Our built-in search analytics give you real-time insight into what your users are looking for.

"Powerful api" is the primary reason why developers consider Elasticsearch over the competitors, whereas "Very easy setup and highly customizable for your search" was stated as the key factor in picking Swiftype.

Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.

- No public GitHub repository available -

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 Swiftype?

Swiftype is the easiest way to add great search to your website or mobile application.

Want advice about which of these to choose?Ask the StackShare community!

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What are some alternatives to Elasticsearch and Swiftype?
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.
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.
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.
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.
Splunk
Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data.
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What tools integrate with Elasticsearch?
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    Reviews of Elasticsearch and Swiftype
    Review ofSwiftypeSwiftype

    We integrated the swiftype technology into our website. Initial setup was super easy and the service has been amazing so far. Swiftype dashboard offers many services to help you understand and optimize the search experience for your users. I highly recommend Swiftype to any website or app that needs an easy to setup, powerful and reliable search solution. The sales and the support team are amazing! Tip, if you want to try out the system, ask for Lucy Yu. She is amazing and walking you through the process!

    How developers use Elasticsearch and Swiftype
    Avatar of imgur
    imgur uses ElasticsearchElasticsearch

    Elasticsearch is the engine that powers search on the site. From a high level perspective, it’s a Lucene wrapper that exposes Lucene’s 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’t 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’t 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.

    How much does Elasticsearch cost?
    How much does Swiftype cost?