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ElasticSearch VS memcached

Compare ElasticSearch VS memcached and see what are their differences

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ElasticSearch logo ElasticSearch

Elasticsearch is an open source, distributed, RESTful search engine.

memcached logo memcached

High-performance, distributed memory object caching system
  • ElasticSearch Landing page
    Landing page //
    2023-10-10
  • memcached Landing page
    Landing page //
    2023-07-23

ElasticSearch features and specs

  • Scalability
    ElasticSearch is highly scalable, allowing you to handle large volumes of data and distribute indexing and search tasks across multiple nodes.
  • Real-Time Data
    It provides real-time indexing and searching capabilities, making it suitable for applications that require up-to-the-minute data retrieval and analysis.
  • Full-Text Search
    ElasticSearch is well-known for its powerful full-text search capabilities, enabling complex search queries and supporting a wide range of search options.
  • Complex Query Support
    It offers a rich query language allowing for complex and nested searching with filters, aggregations, and more.
  • Distributed Architecture
    ElasticSearch is designed to be distributed by nature, making it resilient to node failures and allowing data and search requests to be distributed across a cluster.
  • Open Source
    ElasticSearch is open-source, offering flexibility and a large community of developers that contribute to its continuous improvement and support.
  • Analytics
    Besides search, it also supports powerful analytics and visualization tools, especially when integrated with Kibana, its visualization dashboard.
  • Integrations
    ElasticSearch can easily integrate with various data sources and frameworks, enhancing its usability across different applications.

Possible disadvantages of ElasticSearch

  • Complexity
    Operating ElasticSearch can be complex, particularly when dealing with large-scale deployments, requiring specialized knowledge and expertise.
  • Resource Intensive
    ElasticSearch can be resource-intensive, requiring significant amounts of RAM and CPU, which can be costly for large-scale operations.
  • Consistency
    As a distributed system, ElasticSearch can sometimes face consistency issues, especially in scenarios involving partitions or network failures.
  • Security
    Though security features are available, they often require additional configurations and are more robust in the paid versions, which can be a concern for open-source users.
  • Cost
    While the core ElasticSearch software is open-source, scaling and additional features (like security, monitoring, and machine learning) are part of the paid Elastic Stack offerings.
  • Learning Curve
    There is a steep learning curve associated with mastering ElasticSearch and its query DSL (Domain Specific Language), which can be a barrier for new users.
  • Maintenance
    Properly maintaining an ElasticSearch cluster requires ongoing management, monitoring, and tuning to ensure optimal performance.
  • Backup and Restore
    Managing backups and restores can be cumbersome and is not as straightforward as in some other databases or data storage solutions.

memcached features and specs

  • High Performance
    Memcached is incredibly fast and efficient at caching data in memory, enabling quick data retrieval and reducing the load on databases. Its in-memory nature significantly reduces latency.
  • Scalability
    Memcached can be easily scaled horizontally by adding more nodes to the caching cluster. This allows it to handle increased loads and large datasets without performance degradation.
  • Simplicity
    Memcached has a simple design and API, making it easy to implement and use. Developers can quickly integrate it into their applications without a steep learning curve.
  • Open Source
    Memcached is free and open-source software, which means it can be used and modified without any licensing fees. This makes it a cost-effective solution for caching.
  • Language Agnostic
    Memcached supports multiple programming languages through various client libraries, making it versatile and suitable for use in diverse tech stacks.

Possible disadvantages of memcached

  • Data Volatility
    Memcached stores data in RAM, so all cached data is lost if the server is restarted or crashes. This makes it unsuitable for storing critical or persistent data.
  • Limited Data Types
    Memcached primarily supports simple key-value pairs. It lacks the rich data types and more complex structures supported by some other caching solutions like Redis.
  • No Persistence
    Memcached does not offer any data persistence features. It cannot save data to disk, so all information is ephemeral and will be lost on system reset.
  • Size Limitation
    Memcached has a memory limit for each instance, thus, large-scale applications may need to manage multiple instances and ensure data is properly distributed.
  • Security
    Memcached does not provide built-in security features such as authentication or encryption. This can be a concern in environments where data privacy and security are critical.

ElasticSearch videos

What is Elasticsearch?

More videos:

  • Review - Real world Elasticsearch Compose/Stack File Review
  • Demo - Elastic Search

memcached videos

Course Preview: Using Memcached and Varnish to Speed Up Your Linux Web App

Category Popularity

0-100% (relative to ElasticSearch and memcached)
Custom Search Engine
100 100%
0% 0
Databases
0 0%
100% 100
Custom Search
100 100%
0% 0
NoSQL Databases
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare ElasticSearch and memcached

ElasticSearch Reviews

Log analysis: Elasticsearch vs Apache Doris
Benchmark tests with ES Rally, the official testing tool for Elasticsearch, showed that Apache Doris was around 5 times as fast as Elasticsearch in data writing, 2.3 times as fast in queries, and it consumed only 1/5 of the storage space that Elasticsearch used. On the test dataset of HTTP logs, it achieved a writing speed of 550 MB/s and a compression ratio of 10:1.
4 Leading Enterprise Search Software to Look For in 2022
“ We’ve built some big data search and mobile desktop applications that help our customers experience fast natural language search. Some applications require this, where I need to find data, I don’t want to build some complex query, I just need to ask the system “help me search for this information, narrow my results” and I don't want to wait several seconds. We’ve built a...
Top 10 Site Search Software Tools & Plugins for 2022
Elasticsearch is built for human users, which means that it’s equipped to handle mistakes that humans often make such as typos. This helps to improve search relevance and enhance the overall search experience. It offers real-time crawling, which automatically detects changes in content and ensures that search results are fresh and relevant.
Best Elasticsearch alternatives for search
However, when it comes to dealing with synonyms (i.e. ‘smart phone’ for ‘Samsung Galaxy’), slang (i.e. ‘kicks’ for ‘Nike Air Jordans’) and context (i.e. ‘car park’ is different to ‘dog park’) – you have to set up a bunch of manual rules/definitions with Elasticsearch and co.
Source: relevance.ai
5 Open-Source Search Engines For your Website
Elasticsearch provides key features like Advanced Full-Text Search Capabilities like Data indexing, Search capabilities including phrases, wildcards, auto suggestions, filters & facets, etc... Elasticsearch can also be used for other use-cases like
Source: vishnuch.tech

memcached Reviews

Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
Quick ask: I don’t see “some” of the other offering out there like MemCached… what was the criteria used to select these? I don’t see any source of how the test where run, specs of the systems, how the DB where set up, etc. Would be very valuable to have in order to attempt to re-validate these test on our own platform. I also came back and saw some of your updates...
Memcached vs Redis - More Different Than You Would Expect
So knowing how the difference between Redis and memcached in-memory usage, lets see what this means. Memcached slabs once assigned never change their size. This means it is possible to poison your memcached cluster and really waste memory. If you load your empty memcached cluster with lots of 1 MB items, then all of the slabs will be allocated to that size. Adding a 80 KB...
Redis vs. Memcached: In-Memory Data Storage Systems
Memcached itself does not support distributed mode. You can only achieve the distributed storage of Memcached on the client side through distributed algorithms such as Consistent Hash. The figure below demonstrates the distributed storage implementation schema of Memcached. Before the client side sends data to the Memcached cluster, it first calculates the target node of the...
Source: medium.com
Why Redis beats Memcached for caching
Both Memcached and Redis are mature and hugely popular open source projects. Memcached was originally developed by Brad Fitzpatrick in 2003 for the LiveJournal website. Since then, Memcached has been rewritten in C (the original implementation was in Perl) and put in the public domain, where it has become a cornerstone of modern Web applications. Current development of...

Social recommendations and mentions

Based on our record, memcached should be more popular than ElasticSearch. It has been mentiond 36 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ElasticSearch mentions (17)

  • ElasticSearch from the Azure store or from Elastic.co?
    What surprised me is that on the Azure store, the only option I see is (Pay as you go), whereas on elastic.co there are the standard platinum and enterprise tiers followed by a where to deploy page and a pricing overview. Source: almost 2 years ago
  • Hunspell on elastic.co cloud
    Can anyone help me how to upload custom hunspell stemmer files to elastic cloud (elastic.co)? According to elastic docs it should go under elasticsearch/config/hunspell, but according to cloud docs I should upload it via features/extension tab. So I tried zipping the hunspell folder and uploading it. I also figured out that it should be in the dictionaries folder, but after uploading it still doesn't work. Source: almost 2 years ago
  • Creating a modern, SaaS website.. what am I missing?
    I can't figure out where I have to go to get more or less of a custom, premium website. I should mention that I look up to websites like elastic.co for example, would be very happy with something like that. I could really use some guidance! Source: about 2 years ago
  • Ask HN: Who is hiring? (October 2022)
    Elastic | Multiple software engineering roles | REMOTE (EMEA) | Full-time | https://elastic.co Elastic offers solutions for security and observability that are built on a single, open technology stack that can be deployed anywhere. Elastic Security enables security teams to prevent, detect, and respond to attacks with a solution built atop the speed and reliable of the Elastic stack. The Security External... - Source: Hacker News / over 2 years ago
  • Seeking clarification about which part of ElasticSearch to use for our website
    I have been trying to digest the elastic.co website to try to understand how we can use elastic search, but I've come to a point where I'm not sure which part of elastic, (if any) makes sense for us. In fact I am royally confused. I wonder if anyone here can help clarify? Source: almost 3 years ago
View more

memcached mentions (36)

  • MySQL Performance Tuning Techniques
    Memcached can help when lightning-fast performance is needed. These tools store frequently accessed data, such as session details, API responses, or product prices, in RAM. This reduces the laid on your primary database, so you can deliver microsecond response times. - Source: dev.to / 2 months ago
  • 10 Best Practices for API Rate Limiting in 2025
    In-memory tools like Redis or Memcached for fast Data retrieval. - Source: dev.to / 3 months ago
  • Outgrowing Postgres: Handling increased user concurrency
    A caching layer using popular in-memory databases like Redis or Memcached can go a long way in addressing Postgres connection overload issues by being able to handle a much larger concurrent request load. Adding a cache lets you serve frequent reads from memory instead, taking pressure off Postgres. - Source: dev.to / 3 months ago
  • API Caching: Techniques for Better Performance
    Memcached — Free and well-known for its simplicity, Memcached is a distributed and powerful memory object caching system. It uses key-value pairs to store small data chunks from database calls, API calls, and page rendering. It is available on Windows. Strings are the only supported data type. Its client-server architecture distributes the cache logic, with half of the logic implemented on the server and the other... - Source: dev.to / 7 months ago
  • story of upgrading rails 5.x to 7.x
    The app depends on several packages to run, so I need to install them locally too. I used a combination of brew and orbstack / docker for installing packages. Some dependencies for this project are redis, mongodb and memcache. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing ElasticSearch and memcached, you can also consider the following products

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Apache Solr - Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Typesense - Typo tolerant, delightfully simple, open source search 🔍

Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.