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  5. Amazon Elasticsearch Service vs Bonsai

Amazon Elasticsearch Service vs Bonsai

OverviewDecisionsComparisonAlternatives

Overview

Bonsai
Bonsai
Stacks27
Followers39
Votes2
Amazon Elasticsearch Service
Amazon Elasticsearch Service
Stacks371
Followers288
Votes24

Amazon Elasticsearch Service vs Bonsai: What are the differences?

Introduction: Amazon Elasticsearch Service and Bonsai are two popular options for managing Elasticsearch clusters for search and analytics purposes. While they both offer similar functionality, there are key differences between the two services.

  1. Hosting Environment: Amazon Elasticsearch Service is a fully managed service provided by Amazon Web Services (AWS), allowing users to easily spin up and manage Elasticsearch clusters within the AWS cloud environment. On the other hand, Bonsai is a third-party service provider that hosts Elasticsearch clusters in various cloud providers such as AWS, Google Cloud, and Azure. This difference in hosting environments can impact factors such as performance, integration, and support options.

  2. Scalability Options: Amazon Elasticsearch Service offers seamless scalability options, allowing users to easily scale their clusters up or down based on demand. It also provides integration with other AWS services for automated scaling. In contrast, Bonsai's scalability options might be limited depending on the cloud provider chosen for hosting. Users may need to manage scaling manually or rely on the capabilities provided by the specific cloud provider.

  3. Cost Structure: The cost structure of Amazon Elasticsearch Service is typically based on a pay-as-you-go model, with pricing determined by factors such as instance type, storage, and data transfer. Bonsai, on the other hand, offers more flexibility in pricing options, including flat-rate plans and volume-based pricing. Depending on the specific needs and budget of the user, one service may be more cost-effective than the other.

  4. Support and Maintenance: Amazon Elasticsearch Service comes with the backing of AWS support, offering various tiers of support options including 24/7 technical support. Bonsai also provides support but the level and responsiveness may vary depending on the plan chosen. Users looking for a robust support system may find Amazon Elasticsearch Service more suitable for their needs.

  5. Customization and Control: While both services offer management of Elasticsearch clusters, Amazon Elasticsearch Service may provide more limitations in terms of customization and control compared to Bonsai. Bonsai allows for more granular control over configuration settings, plugins, and Elasticsearch versions, giving users greater flexibility in tailoring their clusters to specific requirements.

  6. Data Residency and Compliance: Amazon Elasticsearch Service allows users to specify the region in which their data is stored, ensuring compliance with data residency regulations and requirements. Bonsai, being a third-party provider, may have limitations in terms of data residency options depending on the cloud provider chosen for hosting. Users with strict data residency and compliance needs should consider these differences when selecting a service.

In Summary, Amazon Elasticsearch Service offers a fully managed Elasticsearch solution within the AWS cloud environment, providing seamless scalability, robust support options, and data residency compliance. Bonsai, on the other hand, is a third-party service that offers more pricing flexibility, customization control, and scalability limitations depending on the cloud provider chosen.

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Advice on Bonsai, Amazon Elasticsearch Service

Phillip
Phillip

Developer at Coach Align

Mar 18, 2021

Decided

The new pricing model Algolia introduced really sealed the deal for us on this one - much closer to pay-as-you-go. And didn't want to spend time learning more about hosting/optimizing Elasticsearch when that isn't our core business problem - would much rather pay others to solve that problem for us.

40.7k views40.7k
Comments
André
André

Nov 20, 2020

Needs adviceonElasticsearchElasticsearchAmazon DynamoDBAmazon DynamoDB

Hi, community, I'm planning to build a web service that will perform a text search in a data set off less than 3k well-structured JSON objects containing config data. I'm expecting no more than 20 MB of data. The general traits I need for this search are:

  • Typo tolerant (fuzzy query), so it has to match the entries even though the query does not match 100% with a word on that JSON
  • Allow a strict match mode
  • Perform the search through all the JSON values (it can reach 6 nesting levels)
  • Ignore all Keys of the JSON; I'm interested only in the values.

The only thing I'm researching at the moment is Elasticsearch, and since the rest of the stack is on AWS the Amazon ElasticSearch is my favorite candidate so far. Although, the only knowledge I have on it was fetched from some articles and Q&A that I read here and there. Is ElasticSearch a good path for this project? I'm also considering Amazon DynamoDB (which I also don't know of), but it does not look to cover the requirements of fuzzy-search and ignore the JSON properties. Thank you in advance for your precious advice!

60.3k views60.3k
Comments
Ted
Ted

Computer Science

Dec 19, 2020

Review

I think elasticsearch should be a great fit for that use case. Using the AWS version will make your life easier. With such a small dataset you may also be able to use an in process library for searching and possibly remove the overhead of using a database. I don’t if it fits the bill, but you may also want to look into lucene.

I can tell you that Dynamo DB is definitely not a good fit for your use case. There is no fuzzy matching feature and you would need to have an index for each field you want to search or convert your data into a more searchable format for storing in Dynamo, which is something a full text search tool like elasticsearch is going to do for you.

42.9k views42.9k
Comments

Detailed Comparison

Bonsai
Bonsai
Amazon Elasticsearch Service
Amazon Elasticsearch Service

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

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.

The Open Source Advantage- Our service is proudly powered by Elasticsearch and Apache Lucene, the open source industry standard for fast full-text search; Results in Real-Time- Search your site's activity as it happens, with Elasticsearch's cutting-edge real-time updates; High Availability by default; Security by default, including TTS/SSL and Advanced Authentication Controls; One-Click Kibana; By-the-Minute Metrics; Third-party integrations like Datadog; Supported by experts with thousands of hours of hands-on experience with Elasticsearch
-
Statistics
Stacks
27
Stacks
371
Followers
39
Followers
288
Votes
2
Votes
24
Pros & Cons
Pros
  • 2
    Free tier
Pros
  • 10
    Easy setup, monitoring and scaling
  • 7
    Kibana
  • 7
    Document-oriented
Integrations
AWS IAM
AWS IAM
Datadog
Datadog
Heroku
Heroku
Elasticsearch
Elasticsearch

What are some alternatives to Bonsai, Amazon Elasticsearch Service?

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).

Algolia

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.

Typesense

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

Amazon CloudSearch

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Manticore Search

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

Azure Search

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

Swiftype

Swiftype

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

MeiliSearch

MeiliSearch

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

Quickwit

Quickwit

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.

Azure Cognitive Search

Azure Cognitive Search

It is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade and AI services across vision, language and speech. Spend more time innovating and less time maintaining a complex cloud search solution.

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