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  1. Stackups
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  4. Cloud Storage
  5. Amazon S3 vs Microsoft SQL Server vs NSQ

Amazon S3 vs Microsoft SQL Server vs NSQ

OverviewDecisionsComparisonAlternatives

Overview

Amazon S3
Amazon S3
Stacks55.1K
Followers40.2K
Votes2.0K
Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
NSQ
NSQ
Stacks142
Followers356
Votes148

Amazon S3 vs Microsoft SQL Server vs NSQ: What are the differences?

Comparison between Amazon S3, Microsoft SQL Server, and NSQ

Amazon S3, Microsoft SQL Server, and NSQ are three popular technologies used for different purposes. In this comparison, we will focus on the key differences between Amazon S3 and Microsoft SQL Server, as well as between Amazon S3 and NSQ.

Amazon S3 vs Microsoft SQL Server

  1. Data Structure: Amazon S3 is an object storage service that works with unstructured data, while Microsoft SQL Server is a relational database management system that stores structured data in a tabular format with defined relationships between tables.

  2. Data Manipulation: Amazon S3 provides a simple key-value interface for data access, enabling operations like storing, retrieving, and deleting objects. On the other hand, Microsoft SQL Server allows complex CRUD operations through SQL queries, including retrieving, inserting, updating, and deleting data from structured tables.

  3. Scalability: Amazon S3 is highly scalable and can support an almost unlimited amount of data storage, making it suitable for storing large amounts of unstructured data. Microsoft SQL Server, while scalable to an extent, has limitations in terms of maximum database size and performance as the data and workload grow.

  4. Data Consistency: Amazon S3 guarantees eventual consistency, meaning updates and deletes may take some time to propagate across all storage locations. In contrast, Microsoft SQL Server provides immediate consistency, ensuring that changes made to the database are immediately reflected and visible to all users.

  5. Data Querying: Amazon S3 does not provide built-in querying capabilities, requiring users to add additional data access or query services on top of it. Microsoft SQL Server, being a relational database, offers powerful query capabilities using SQL, allowing users to easily retrieve and manipulate data based on specific filtering and aggregation conditions.

  6. Data Backup and Recovery: Amazon S3 automatically replicates data across multiple locations to ensure durability and high availability. It also offers versioning, allowing retrieval of previous versions of objects. Microsoft SQL Server offers backup and restore functionalities, allowing users to create regular backups and restore the database to a specific point in time.

Amazon S3 vs NSQ

  1. Data Structure: Amazon S3 stores unstructured data as objects, whereas NSQ is a message queuing system used for passing messages between distributed components or microservices.

  2. Messaging Protocol: Amazon S3 uses a simple RESTful API for manipulating objects, while NSQ relies on an efficient, lightweight TCP-based messaging protocol, enabling asynchronous communication and decoupling of components.

  3. Message Delivery Guarantees: Amazon S3 offers strong durability and availability guarantees, as it automatically replicates and distributes objects across multiple storage locations. In contrast, NSQ provides at-least-once message delivery semantics, ensuring that messages are delivered to consumers but not guaranteeing that they are processed only once.

  4. Message Ordering: Amazon S3 does not provide built-in support for maintaining message ordering, as it primarily focuses on object storage. NSQ, however, has built-in support for ordered message delivery, ensuring that messages are processed in the same order they were received.

  5. Message Persistence: Amazon S3 is designed for durable object storage, ensuring long-term persistence even if the system or components go offline. NSQ, while persistent to some extent, relies on an ephemeral message storage strategy, where messages are kept in memory or disk temporarily before being delivered to consumers.

  6. Scalability: Amazon S3 is highly scalable and can handle large volumes of data and requests. NSQ is also scalable and can handle high throughput, but it may require additional configurations and setups for distributed message processing and load balancing.

In summary, Amazon S3 is a scalable object storage service that works with unstructured data, offering simple key-value access and robust durability. Microsoft SQL Server, on the other hand, is a relational database management system focusing on structured data, providing powerful querying capabilities and immediate consistency. NSQ is a distributed messaging system designed for passing messages between components, offering efficient message delivery and ordering guarantees.

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Advice on Amazon S3, Microsoft SQL Server, NSQ

Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
668k views668k
Comments
Mohammad
Mohammad

Aug 30, 2020

Needs adviceonBackblaze B2 Cloud StorageBackblaze B2 Cloud StoragePHPPHPLaravelLaravel

Hello! I have a mobile app with nearly 100k MAU, and I want to add a cloud file storage service to my app.

My app will allow users to store their image, video, and audio files and retrieve them to their device when necessary.

I have already decided to use PHP & Laravel as my backend, and I use Contabo VPS. Now, I need an object storage service for my app, and my options are:

  • Amazon S3 : It sounds to me like the best option but the most expensive. Closest to my users (MENA Region) for other services, I will have to go to Europe. Not sure how important this is?

  • DigitalOcean Spaces : Seems like my best option for price/service, but I am still not sure

  • Wasabi: the best price (6 USD/MONTH/TB) and free bandwidth, but I am not sure if it fits my needs as I want to allow my users to preview audio and video files. They don't recommend their service for streaming videos.

  • Backblaze B2 Cloud Storage: Good price but not sure about them.

  • There is also the self-hosted s3 compatible option, but I am not sure about that.

Any thoughts will be helpful. Also, if you think I should post in a different sub, please tell me.

180k views180k
Comments
Gabriel
Gabriel

CEO at NaoLogic Inc

Dec 24, 2019

Decided

We offer our customer HIPAA compliant storage. After analyzing the market, we decided to go with Google Storage. The Nodejs API is ok, still not ES6 and can be very confusing to use. For each new customer, we created a different bucket so they can have individual data and not have to worry about data loss. After 1000+ customers we started seeing many problems with the creation of new buckets, with saving or retrieving a new file. Many false positive: the Promise returned ok, but in reality, it failed.

That's why we switched to S3 that just works.

330k views330k
Comments

Detailed Comparison

Amazon S3
Amazon S3
Microsoft SQL Server
Microsoft SQL Server
NSQ
NSQ

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

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

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.
-
support distributed topologies with no SPOF;horizontally scalable (no brokers, seamlessly add more nodes to the cluster);low-latency push based message delivery (performance);combination load-balanced and multicast style message routing;excel at both streaming (high-throughput) and job oriented (low-throughput) workloads;primarily in-memory (beyond a high-water mark messages are transparently kept on disk);runtime discovery service for consumers to find producers (nsqlookupd);transport layer security (TLS);data format agnostic;few dependencies (easy to deploy) and a sane, bounded, default configuration;simple TCP protocol supporting client libraries in any language;HTTP interface for stats, admin actions, and producers (no client library needed to publish);integrates with statsd for realtime instrumentation;robust cluster administration interface (nsqadmin)
Statistics
Stacks
55.1K
Stacks
21.3K
Stacks
142
Followers
40.2K
Followers
15.5K
Followers
356
Votes
2.0K
Votes
540
Votes
148
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
    Takes time/work to organize buckets & folders properly
  • 6
    Requires a credit card
  • 3
    Complex to set up
Pros
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
Cons
  • 4
    Expensive Licensing
  • 2
    Microsoft
  • 1
    Allwayon can loose data in asycronious mode
  • 1
    Data pages is only 8k
  • 1
    The maximum number of connections is only 14000 connect
Pros
  • 29
    It's in golang
  • 20
    Lightweight
  • 20
    Distributed
  • 18
    Easy setup
  • 17
    High throughput
Cons
  • 1
    Get NSQ behavior out of Kafka but not inverse
  • 1
    Long term persistence
  • 1
    HA

What are some alternatives to Amazon S3, Microsoft SQL Server, NSQ?

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.

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

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.

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