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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cloud Storage
  5. Amazon S3 vs Oracle vs Redis

Amazon S3 vs Oracle vs Redis

OverviewDecisionsComparisonAlternatives

Overview

Amazon S3
Amazon S3
Stacks55.1K
Followers40.2K
Votes2.0K
Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6

Amazon S3 vs Oracle vs Redis: What are the differences?

Introduction: In the realm of cloud storage and database management systems, Amazon S3, Oracle, and Redis are three prominent players. Understanding the key differences between them is crucial for decision-making in various IT projects.

  1. Storage Type: Amazon S3 is an object storage service, suitable for storing vast amounts of unstructured data, while Oracle is a relational database management system designed for structured data storage. Redis, on the other hand, is an in-memory data store used for caching and real-time data processing, making it ideal for applications requiring low latency.

  2. Scalability: When it comes to scalability, Amazon S3 offers virtually unlimited scalability by automatically distributing data across multiple servers. Oracle, despite being scalable, usually requires manual intervention and careful planning to scale efficiently. Redis excels at horizontal scalability, allowing for easy distribution of data across multiple nodes.

  3. Data Consistency: Oracle, being a traditional relational database system, ensures strong consistency, making it suitable for applications that require transactional integrity. Amazon S3, being an object store, is eventually consistent, meaning data may not be immediately consistent across all regions. Redis offers eventual consistency by default but can be configured for stronger consistency if needed.

  4. Data Retrieval Speed: Redis, being an in-memory data store, offers exceptionally fast data retrieval speeds compared to Amazon S3 and Oracle, making it a preferred choice for applications requiring real-time processing and analysis. Amazon S3, due to its nature as object storage, may experience higher latency compared to Redis and Oracle in certain use cases.

  5. Cost Structure: Amazon S3 operates on a pay-as-you-go model, where users pay based on storage used, data transfer, and requests made to the service. Oracle typically involves upfront costs for licenses and ongoing maintenance fees. Redis, being open-source, provides a cost-effective solution for in-memory data storage and processing needs.

  6. Use Cases: Amazon S3 is well-suited for storing large volumes of data, backups, and serving static assets for websites. Oracle is commonly used for enterprise applications requiring structured data management, such as financial systems or CRM. Redis finds its strengths in caching, session storage, real-time analytics, and message queues due to its high-speed data retrieval capabilities.

In Summary, understanding the key differences between Amazon S3, Oracle, and Redis is crucial in selecting the most suitable solution for specific storage and database management needs in IT projects.

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Advice on Amazon S3, Oracle, Redis

Daniel
Daniel

Data Engineer at Dimensigon

Jul 18, 2020

Decided

We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.

495k views495k
Comments
Abigail
Abigail

Dec 6, 2019

Decided

In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.

MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.

Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.

540k views540k
Comments
Abigail
Abigail

Dec 10, 2019

Decided

We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.

558k views558k
Comments

Detailed Comparison

Amazon S3
Amazon S3
Oracle
Oracle
Redis
Redis

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

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Write, read, and delete objects containing from 1 byte to 5 terabytes of data each. The number of objects you can store is unlimited.;Each object is stored in a bucket and retrieved via a unique, developer-assigned key.;A bucket can be stored in one of several Regions. You can choose a Region to optimize for latency, minimize costs, or address regulatory requirements. Amazon S3 is currently available in the US Standard, US West (Oregon), US West (Northern California), EU (Ireland), Asia Pacific (Singapore), Asia Pacific (Tokyo), Asia Pacific (Sydney), South America (Sao Paulo), and GovCloud (US) Regions. The US Standard Region automatically routes requests to facilities in Northern Virginia or the Pacific Northwest using network maps.;Objects stored in a Region never leave the Region unless you transfer them out. For example, objects stored in the EU (Ireland) Region never leave the EU.;Authentication mechanisms are provided to ensure that data is kept secure from unauthorized access. Objects can be made private or public, and rights can be granted to specific users.;Options for secure data upload/download and encryption of data at rest are provided for additional data protection.;Uses standards-based REST and SOAP interfaces designed to work with any Internet-development toolkit.;Built to be flexible so that protocol or functional layers can easily be added. The default download protocol is HTTP. A BitTorrent protocol interface is provided to lower costs for high-scale distribution.;Provides functionality to simplify manageability of data through its lifetime. Includes options for segregating data by buckets, monitoring and controlling spend, and automatically archiving data to even lower cost storage options. These options can be easily administered from the Amazon S3 Management Console.;Reliability backed with the Amazon S3 Service Level Agreement.
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Statistics
GitHub Stars
-
GitHub Stars
-
GitHub Stars
42
GitHub Forks
-
GitHub Forks
-
GitHub Forks
6
Stacks
55.1K
Stacks
2.6K
Stacks
61.9K
Followers
40.2K
Followers
1.8K
Followers
46.5K
Votes
2.0K
Votes
113
Votes
3.9K
Pros & Cons
Pros
  • 590
    Reliable
  • 492
    Scalable
  • 456
    Cheap
  • 329
    Simple & easy
  • 83
    Many sdks
Cons
  • 7
    Permissions take some time to get right
  • 6
    Requires a credit card
  • 6
    Takes time/work to organize buckets & folders properly
  • 3
    Complex to set up
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Expensive
  • 5
    Hard to maintain
Cons
  • 14
    Expensive
Pros
  • 888
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
Cons
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL

What are some alternatives to Amazon S3, Oracle, Redis?

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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