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  1. Stackups
  2. Utilities
  3. Caching
  4. Managed Memcache
  5. Amazon ElastiCache vs Couchbase

Amazon ElastiCache vs Couchbase

OverviewDecisionsComparisonAlternatives

Overview

Amazon ElastiCache
Amazon ElastiCache
Stacks1.3K
Followers1.0K
Votes151
Couchbase
Couchbase
Stacks505
Followers606
Votes110

Amazon ElastiCache vs Couchbase: What are the differences?

Introduction:

Amazon ElastiCache and Couchbase are both popular in-memory caching solutions used by developers to improve the performance and scalability of their applications. However, these two services have some key differences that set them apart from each other. In this article, we will explore six major differences between Amazon ElastiCache and Couchbase.

1. Scalability: Amazon ElastiCache is a managed service that offers automatic scalability. It allows you to easily add or remove cache nodes as per your application's needs. On the other hand, Couchbase requires manual configuration and sharding for scalability, making it more complex to set up and manage.

2. Data Persistence: Couchbase provides support for a flexible data model, allowing you to store and query JSON documents directly. It also offers built-in replication and high availability features, ensuring data durability. In contrast, Amazon ElastiCache does not provide data persistence. It is primarily used for caching frequently accessed data rather than as a storage solution.

3. Multi-Region Support: Couchbase has native support for multi-region deployments, enabling you to replicate data across different regions for better availability and disaster recovery. On the other hand, Amazon ElastiCache does not have built-in support for multi-region deployments, although you can set up replication manually using other AWS services like AWS Global Accelerator.

4. Integration with other AWS Services: As an Amazon Web Services (AWS) offering, Amazon ElastiCache seamlessly integrates with various other AWS services like Amazon EC2, AWS Identity and Access Management (IAM), and Amazon CloudWatch. This allows you to leverage the full capabilities of the AWS ecosystem. Couchbase, being a standalone product, does not have the same level of integration with AWS services.

5. Consistency Models: Couchbase provides flexible consistency models, including strong consistency, eventual consistency, and various levels in between. This allows you to choose the appropriate consistency level based on your application's requirements. Amazon ElastiCache, being primarily a caching service, does not offer the same level of consistency options.

6. Pricing Model: The pricing model for Amazon ElastiCache is based on the cache node types and sizes, as well as the data transfer and storage used. Couchbase, on the other hand, follows a subscription-based pricing model that includes licensing costs for the software.

In summary, Amazon ElastiCache and Couchbase differ in terms of scalability, data persistence, multi-region support, integration with other AWS services, consistency models, and pricing model. While Amazon ElastiCache offers automatic scalability, Couchbase requires manual configuration. Couchbase provides support for a flexible data model with built-in replication, while ElastiCache is primarily used for caching. Couchbase has native support for multi-region deployments, whereas ElastiCache requires manual setup. Amazon ElastiCache integrates with other AWS services, while Couchbase is a standalone product. Couchbase offers flexible consistency models, and its pricing is subscription-based, while ElastiCache does not offer the same level of consistency options and follows a different pricing model.

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Advice on Amazon ElastiCache, Couchbase

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

592k views592k
Comments
Mike
Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k
Comments

Detailed Comparison

Amazon ElastiCache
Amazon ElastiCache
Couchbase
Couchbase

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.

Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.

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
JSON document database; N1QL (SQL-like query language); Secondary Indexing; Full-Text Indexing; Eventing/Triggers; Real-Time Analytics; Mobile Synchronization for offline support; Autonomous Operator for Kubernetes and OpenShift
Statistics
Stacks
1.3K
Stacks
505
Followers
1.0K
Followers
606
Votes
151
Votes
110
Pros & Cons
Pros
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
Pros
  • 18
    Flexible data model, easy scalability, extremely fast
  • 18
    High performance
  • 9
    Mobile app support
  • 7
    You can query it with Ansi-92 SQL
  • 6
    All nodes can be read/write
Cons
  • 3
    Terrible query language
Integrations
No integrations available
Hadoop
Hadoop
Kafka
Kafka
Elasticsearch
Elasticsearch
Kubernetes
Kubernetes
Apache Spark
Apache Spark

What are some alternatives to Amazon ElastiCache, Couchbase?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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