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  5. Amazon Elasticsearch Service vs Found Elasticsearch

Amazon Elasticsearch Service vs Found Elasticsearch

OverviewDecisionsComparisonAlternatives

Overview

Found Elasticsearch
Found Elasticsearch
Stacks11
Followers15
Votes0
Amazon Elasticsearch Service
Amazon Elasticsearch Service
Stacks371
Followers288
Votes24

Amazon Elasticsearch Service vs Found Elasticsearch: What are the differences?

Amazon Elasticsearch Service: Real-time, distributed search and analytics engine that fits nicely into a cloud environment. ; Found Elasticsearch: Hosted Elasticsearch. Create your own fully managed and hosted Elasticsearch cluster. You get a dedicated cluster with reserved memory, giving you predictable performance. There are no arbitrary limits on how many indexes or documents you can store. Scale your clusters as and when needed, without any downtime.

Amazon Elasticsearch Service and Found Elasticsearch belong to "Search as a Service" category of the tech stack.

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Advice on Found Elasticsearch, 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

Found Elasticsearch
Found Elasticsearch
Amazon Elasticsearch Service
Amazon Elasticsearch Service

Create your own fully managed and hosted Elasticsearch cluster. You get a dedicated cluster with reserved memory, giving you predictable performance. There are no arbitrary limits on how many indexes or documents you can store. Scale your clusters as and when needed, without any downtime.

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.

Hosted and managed: You get your own fully hosted and managed Elasticsearch cluster. No need to host and maintain your own costly search infrastructure.; Reserved Memory and storage: Your clusters get reserved memory and storage. No shared clusters and no arbitrary limits on how many indexes or documents you can store.; Scalable and flexible: Start small, grow big. You can scale your cluster as and when needed, without any downtime. There are several Elasticsearch versions to choose from, and upgrading is easier than ever.; Developer friendly: Our HTTPS API is developer-friendly and existing Elasticsearch libraries such as Tire, PyES and others works out of the box. We even provide an unmodified Elasticsearch API, so for those who have an existing Elasticsearch integration it is easy to start using Found.; Security: Communication to and from our service is securely transmitted over HTTPS (SSL) and your data is stored behind multiple firewalls and proxies. All clusters run in isolated containers (LXC) and customizable ACLs allow for restricting access to trusted people and hosts.; Availability: For production and mission critical environments we provide replication and automatic failover, protecting your cluster against unplanned downtime. In addition, data is continuously backed up to Amazon S3. In the event of a datacenter failure, your cluster is automatically failed over to a working datacenter or, in the case of a catastrophic event, rebuilt from backup.; Multi region: Found Elasticsearch is available in multiple regions.; Found Elasticsearch is also available on Heroku, AppHarbor and CloudControl.
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Statistics
Stacks
11
Stacks
371
Followers
15
Followers
288
Votes
0
Votes
24
Pros & Cons
No community feedback yet
Pros
  • 10
    Easy setup, monitoring and scaling
  • 7
    Kibana
  • 7
    Document-oriented
Integrations
No integrations available
Elasticsearch
Elasticsearch

What are some alternatives to Found Elasticsearch, 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.

Bonsai

Bonsai

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.

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