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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cloud Storage
  5. Amazon EBS vs MongoDB

Amazon EBS vs MongoDB

OverviewComparisonAlternatives

Overview

Amazon EBS
Amazon EBS
Stacks650
Followers542
Votes82
MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K

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Detailed Comparison

Amazon EBS
Amazon EBS
MongoDB
MongoDB

Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage.

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.

Amazon EBS allows you to create storage volumes from 1 GB to 1 TB that can be mounted as devices by Amazon EC2 instances. Multiple volumes can be mounted to the same instance.;Amazon EBS enables you to provision a specific level of I/O performance if desired, by choosing a Provisioned IOPS volume. This allows you to predictably scale to thousands of IOPS per Amazon EC2 instance.;Storage volumes behave like raw, unformatted block devices, with user supplied device names and a block device interface. You can create a file system on top of Amazon EBS volumes, or use them in any other way you would use a block device (like a hard drive).;Amazon EBS volumes are placed in a specific Availability Zone, and can then be attached to instances also in that same Availability Zone.;Each storage volume is automatically replicated within the same Availability Zone. This prevents data loss due to failure of any single hardware component.;Amazon EBS also provides the ability to create point-in-time snapshots of volumes, which are persisted to Amazon S3. These snapshots can be used as the starting point for new Amazon EBS volumes, and protect data for long-term durability. The same snapshot can be used to instantiate as many volumes as you wish. These snapshots can be copied across AWS regions, making it easier to leverage multiple AWS regions for geographical expansion, data center migration and disaster recovery.;AWS also enables you to create new volumes from AWS hosted public data sets.;Amazon CloudWatch exposes performance metrics for EBS volumes, giving you insight into bandwidth, throughput, latency, and queue depth. The metrics are accessible via the AWS CloudWatch API or the AWS Management Console. For more details, see Amazon CloudWatch.
Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
Statistics
GitHub Stars
-
GitHub Stars
27.7K
GitHub Forks
-
GitHub Forks
5.7K
Stacks
650
Stacks
96.6K
Followers
542
Followers
82.0K
Votes
82
Votes
4.1K
Pros & Cons
Pros
  • 36
    Point-in-time snapshots
  • 27
    Data reliability
  • 19
    Configurable i/o performance
Pros
  • 829
    Document-oriented storage
  • 594
    No sql
  • 554
    Ease of use
  • 465
    Fast
  • 410
    High performance
Cons
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 2
    Proprietary query language

What are some alternatives to Amazon EBS, MongoDB?

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.

Amazon S3

Amazon S3

Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web

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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