Amazon ElastiCache vs Elasticsearch

Overview

Amazon ElastiCache

Stacks1.3K

Followers1.0K

Votes151

Elasticsearch

Stacks35.5K

Followers27.1K

Votes1.6K

Amazon ElastiCache vs Elasticsearch: What are the differences?

Amazon ElastiCache and Elasticsearch are two popular services provided by AWS. Both services have their own unique features and use cases. It is important to understand the key differences between them in order to choose the appropriate service for specific requirements.

Data Storage Model: Amazon ElastiCache is primarily used as an in-memory data store for structured and unstructured data. It is well-suited for caching and session management. On the other hand, Elasticsearch is a distributed search and analytics engine that allows for full-text search and real-time analytics. It is designed to handle and analyze large volumes of data.
Querying Capabilities: ElastiCache supports key-value-based querying using operations like GET and SET. It is not designed for complex querying. Elasticsearch, on the other hand, offers powerful search capabilities with support for full-text search, fuzzy search, and complex querying using a query DSL (Domain-Specific Language) based on JSON. It allows for advanced text analysis and relevance scoring.
Scalability and High Availability: ElastiCache allows for horizontal scalability by adding or removing cache nodes. It offers high availability through automatic replication and failover. Elasticsearch, on the other hand, is designed to handle large-scale data processing and analytics. It supports horizontal scalability by adding or removing data nodes. It also provides automatic data replication and high availability through sharding and replica management.
Data Persistence: ElastiCache is an in-memory caching service and does not persist data to disk by default. It is primarily used for temporary data storage. Elasticsearch, on the other hand, provides the option to persist data to disk, allowing for long-term storage and analysis. It supports various data storage options, including SSDs and cloud-based storage.
Support for Structured and Unstructured Data: ElastiCache is used for storing and retrieving structured and unstructured data in key-value format. It does not provide advanced indexing or analysis capabilities for unstructured data. Elasticsearch, on the other hand, excels in handling unstructured data by providing advanced indexing and analysis features like analyzers, tokenizers, and aggregations. It supports JSON-based document storage and indexing.
Integration with Other AWS Services: ElastiCache integrates well with other AWS services like Amazon RDS and Amazon EC2. It can be used to offload read operations from a relational database or to store session data for web applications. Elasticsearch also integrates with other AWS services and provides plugins for data ingestion from various sources like S3, Kinesis, and CloudWatch. It can be used for log analytics, real-time monitoring, and business intelligence applications.

In summary, Amazon ElastiCache is primarily used as an in-memory caching service for structured and unstructured data, while Elasticsearch is a distributed search and analytics engine that excels in handling large volumes of unstructured data with advanced indexing and analysis capabilities. ElastiCache focuses on high-performance caching and session management, while Elasticsearch offers powerful search capabilities and real-time analytics.

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Advice on Amazon ElastiCache, Elasticsearch

Rana Usman

Chief Technology Officer at TechAvanza

Jun 4, 2020

Needs adviceon

Firebase

Elasticsearch

Algolia

Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?

(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.

Thank you!

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Detailed Comparison

Amazon ElastiCache	Elasticsearch
ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis.	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).
Support for two engines: Memcached and Redis;Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.;Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.;Detailed monitoring statistics for the engine nodes at no extra cost via Amazon CloudWatch;Pay only for the resources you consume based on node hours used	Distributed and Highly Available Search Engine;Multi Tenant with Multi Types;Various set of APIs including RESTful;Clients available in many languages including Java, Python, .NET, C#, Groovy, and more;Document oriented;Reliable, Asynchronous Write Behind for long term persistency;(Near) Real Time Search;Built on top of Apache Lucene;Per operation consistency;Inverted indices with finite state transducers for full-text querying;BKD trees for storing numeric and geo data;Column store for analytics;Compatible with Hadoop using the ES-Hadoop connector;Open Source under Apache 2 and Elastic License
Statistics
Stacks 1.3K	Stacks 35.5K
Followers 1.0K	Followers 27.1K
Votes 151	Votes 1.6K
Pros & Cons
Pros 58 Redis 32 High-performance 26 Backed by amazon 21 Memcached 14 Elastic	Pros 329 Powerful api 315 Great search engine 231 Open source 214 Restful 200 Near real-time search Cons 7 Resource hungry 6 Diffecult to get started 5 Expensive 4 Hard to keep stable at large scale
Integrations
No integrations available	Kibana Beats Logstash

What are some alternatives to Amazon ElastiCache, Elasticsearch?

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.

MemCachier

MemCachier provides an easy and powerful managed caching solution for all your performance and scalability needs. It works with the ubiquitous memcache protocol so your favourite language and framework already supports it.

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 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

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.

Memcached Cloud

Memcached Cloud is a fully-managed service for running your Memcached in a reliable and fail-safe manner. Your dataset is constantly replicated, so if a node fails, an auto-switchover mechanism guarantees data is served without interruption. Memcached Cloud provides various data persistence options as well as remote backups for disaster recovery purposes.

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

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.

Related Comparisons

Amazon ElastiCache vs Elasticsearch: What are the differences?

Data Storage Model: Amazon ElastiCache is primarily used as an in-memory data store for structured and unstructured data. It is well-suited for caching and session management. On the other hand, Elasticsearch is a distributed search and analytics engine that allows for full-text search and real-time analytics. It is designed to handle and analyze large volumes of data.
Querying Capabilities: ElastiCache supports key-value-based querying using operations like GET and SET. It is not designed for complex querying. Elasticsearch, on the other hand, offers powerful search capabilities with support for full-text search, fuzzy search, and complex querying using a query DSL (Domain-Specific Language) based on JSON. It allows for advanced text analysis and relevance scoring.
Scalability and High Availability: ElastiCache allows for horizontal scalability by adding or removing cache nodes. It offers high availability through automatic replication and failover. Elasticsearch, on the other hand, is designed to handle large-scale data processing and analytics. It supports horizontal scalability by adding or removing data nodes. It also provides automatic data replication and high availability through sharding and replica management.
Data Persistence: ElastiCache is an in-memory caching service and does not persist data to disk by default. It is primarily used for temporary data storage. Elasticsearch, on the other hand, provides the option to persist data to disk, allowing for long-term storage and analysis. It supports various data storage options, including SSDs and cloud-based storage.
Support for Structured and Unstructured Data: ElastiCache is used for storing and retrieving structured and unstructured data in key-value format. It does not provide advanced indexing or analysis capabilities for unstructured data. Elasticsearch, on the other hand, excels in handling unstructured data by providing advanced indexing and analysis features like analyzers, tokenizers, and aggregations. It supports JSON-based document storage and indexing.
Integration with Other AWS Services: ElastiCache integrates well with other AWS services like Amazon RDS and Amazon EC2. It can be used to offload read operations from a relational database or to store session data for web applications. Elasticsearch also integrates with other AWS services and provides plugins for data ingestion from various sources like S3, Kinesis, and CloudWatch. It can be used for log analytics, real-time monitoring, and business intelligence applications.

Amazon ElastiCache vs Elasticsearch

Overview