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  4. Search As A Service
  5. Amazon CloudSearch vs Lucene

Amazon CloudSearch vs Lucene

OverviewComparisonAlternatives

Overview

Amazon CloudSearch
Amazon CloudSearch
Stacks130
Followers152
Votes27
Lucene
Lucene
Stacks175
Followers230
Votes2

Amazon CloudSearch vs Lucene: What are the differences?

Introduction

Amazon CloudSearch and Lucene are both powerful search solutions that are widely used in the industry. While they share similarities in terms of providing search functionality, there are key differences between the two that make them suitable for different use cases. In this article, we will explore six key differences between Amazon CloudSearch and Lucene.

  1. Managed vs. self-hosted: Amazon CloudSearch is a fully managed search service provided by Amazon Web Services (AWS). This means that AWS takes care of the infrastructure, maintenance, and scalability aspects, allowing developers to focus on the search implementation. On the other hand, Lucene is a self-hosted search library that needs to be integrated into the application and requires manual administration and setup.

  2. Scalability: Amazon CloudSearch offers seamless scalability out-of-the-box. It automatically scales to handle increasing data volumes and traffic without any manual intervention required. In contrast, Lucene requires manual configuration and careful capacity planning to ensure optimum performance and scalability as the data and query volumes grow.

  3. Full-text search features: Amazon CloudSearch provides advanced full-text search capabilities, such as stemming, synonym expansion, and language-specific analysis. These features help in improving the relevance of search results and delivering a better search experience to users. While Lucene also provides similar functionalities, they may require additional customization and development effort to implement.

  4. Query flexibility: Amazon CloudSearch uses a simplified query language that allows developers to easily construct complex search queries using Boolean operators, range searches, and more. Lucene, on the other hand, provides a more powerful query language, allowing developers to perform fine-grained control over search operations, including proximity searches, wildcard searches, and custom scoring algorithms.

  5. Indexing options: Amazon CloudSearch automatically indexes the data using predefined data types, eliminating the need for manual schema management. It supports various data sources, including JSON and XML, making it easy to index structured and unstructured data. In contrast, Lucene requires developers to define the schema and indexing strategy explicitly, providing more control over the indexing process.

  6. Integration with other AWS services: Amazon CloudSearch seamlessly integrates with other AWS services, such as Amazon S3, Amazon RDS, and Amazon EC2, allowing developers to build comprehensive search solutions using a combination of services. Lucene, being a standalone library, requires manual integration and customization with other services, which may need additional effort and expertise.

In summary, Amazon CloudSearch offers a managed and scalable search service with advanced full-text search features and seamless integration with other AWS services, while Lucene provides fine-grained query control and indexing flexibility but requires manual setup and administration. The choice between the two depends on the specific requirements and resources available for implementing search functionality in an application.

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Detailed Comparison

Amazon CloudSearch
Amazon CloudSearch
Lucene
Lucene

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.

Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.

Simple to Configure – You can make your data searchable using the AWS Management Console, API calls, or command line tools. Simply point to a sample set of data, and Amazon CloudSearch automatically proposes a list of index fields and a suggested configuration.;Automatic Scaling For Data & Traffic – Amazon CloudSearch scales up and down seamlessly as the amount of data or query volume changes.;Low Latency, High Throughput – Amazon CloudSearch always stores your index in RAM to ensure low latency and high throughput performance even at large scale. Amazon CloudSearch was created from the same A9 technology that powers search on Amazon.com.;Rich Search Features – Amazon CloudSearch indexes and searches both structured data and plain text. It includes most search features that developers have come to expect from a search engine, such as faceted search, free text search, Boolean search, customizable relevance ranking, query time rank expressions, field weighting, and sorting of results using any field. Amazon CloudSearch also provides near real-time indexing of document updates.;Secure – Amazon CloudSearch uses strong cryptographic methods to authenticate users and prevent unauthorized control of your domains. Amazon CloudSearch supports HTTPS and includes web service interfaces to configure firewall settings that control network access to your domain.
over 150GB/hour on modern hardware;small RAM requirements -- only 1MB heap;incremental indexing as fast as batch indexing;index size roughly 20-30% the size of text indexed;ranked searching -- best results returned first;many powerful query types: phrase queries, wildcard queries, proximity queries, range queries;fielded searching (e.g. title, author, contents);sorting by any field;multiple-index searching with merged results;allows simultaneous update and searching;flexible faceting, highlighting, joins and result grouping;fast, memory-efficient and typo-tolerant suggesters;pluggable ranking models, including the Vector Space Model and Okapi BM25;configurable storage engine (codecs)
Statistics
Stacks
130
Stacks
175
Followers
152
Followers
230
Votes
27
Votes
2
Pros & Cons
Pros
  • 12
    Managed
  • 7
    Auto-Scaling
  • 5
    Compound Queries
  • 3
    Easy Setup
Pros
  • 1
    Fast
  • 1
    Small
Integrations
No integrations available
Solr
Solr
Java
Java

What are some alternatives to Amazon CloudSearch, Lucene?

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.

Sphinx

Sphinx

It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.

Amazon Elasticsearch Service

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.

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.

MkDocs

MkDocs

It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.

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.

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