Amazon CloudSearch聽vs聽Amazon Elasticsearch Service

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

Amazon CloudSearch: Set up, manage, and scale a search solution for your website or application. 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; Amazon Elasticsearch Service: Real-time, distributed search and analytics engine that fits nicely into a cloud environment. .

Amazon CloudSearch and Amazon Elasticsearch Service can be primarily classified as "Search as a Service" tools.

"Managed" is the top reason why over 6 developers like Amazon CloudSearch, while over 7 developers mention "Easy setup, monitoring and scaling" as the leading cause for choosing Amazon Elasticsearch Service.

esa, Zola, and Firecracker are some of the popular companies that use Amazon Elasticsearch Service, whereas Amazon CloudSearch is used by GravityDev, Publitas, and AgoraPulse. Amazon Elasticsearch Service has a broader approval, being mentioned in 79 company stacks & 13 developers stacks; compared to Amazon CloudSearch, which is listed in 16 company stacks and 6 developer stacks.

Advice on Amazon CloudSearch and Amazon Elasticsearch Service
Andr茅 Ribeiro
at Federal University of Rio de Janeiro | 4 upvotes 路 15.1K views

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!

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Replies (3)
Ted Elliott

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鈥檛 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.

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Julien DeFrance
Principal Software Engineer at Tophatter | 3 upvotes 路 9K views

The Amazon Elastic Search service will certainly help you do most of the heavy lifting and you won't have to maintain any of the underlying infrastructure. However, elastic search isn't trivial in nature. Typically, this will mean several days worth of work.

Over time and projects, I've over the years leveraged another solution called Algolia Search. Algolia is a fully managed, search as a service solution, which also has SDKs available for most common languages, will answer your fuzzy search requirements, and also cut down implementation and maintenance costs significantly. You should be able to get a solution up and running within a couple of minutes to an hour.

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Roel van den Brand
Lead Developer at Di-Vision Consultion | 3 upvotes 路 10.3K views
Recommends
Amazon Athena

Maybe you can do it with storing on S3, and query via Amazon Athena en AWS Glue. Don't know about the performance though. Fuzzy search could otherwise be done with storing a soundex value of the fields you want to search on in a MongoDB. In DynamoDB you would need indexes on every searchable field if you want it to be efficient.

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Decisions about Amazon CloudSearch and Amazon Elasticsearch Service
Phillip Manwaring
Developer at Coach Align | 5 upvotes 路 10.8K views

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.

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Pros of Amazon CloudSearch
Pros of Amazon Elasticsearch Service
  • 10
    Managed
  • 7
    Auto-Scaling
  • 5
    Compound Queries
  • 3
    Easy Setup
  • 10
    Easy setup, monitoring and scaling
  • 7
    Document-oriented
  • 6
    Kibana

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What is 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.

What is 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.

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What companies use Amazon CloudSearch?
What companies use Amazon Elasticsearch Service?
See which teams inside your own company are using Amazon CloudSearch or Amazon Elasticsearch Service.
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What are some alternatives to Amazon CloudSearch and Amazon Elasticsearch Service?
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.
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).
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.
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.
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.
See all alternatives