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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. CouchDB vs Microsoft SQL Server

CouchDB vs Microsoft SQL Server

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K

CouchDB vs Microsoft SQL Server: What are the differences?

# Introduction
This markdown highlights the key differences between CouchDB and Microsoft SQL Server.

1. **Data Model**: CouchDB follows a document-oriented data model where each record is a JSON document, allowing for flexibility in schema design, while Microsoft SQL Server uses a relational data model with structured tables and defined relationships.
2. **Scalability**: CouchDB is designed to be distributed from the ground up, allowing for easy horizontal scaling by adding more nodes, whereas Microsoft SQL Server traditionally requires vertical scaling through more powerful hardware.
3. **Consistency**: CouchDB offers eventual consistency, where changes are propagated to all nodes eventually, providing better availability and fault tolerance, while Microsoft SQL Server supports strong consistency by default for transactional data integrity.
4. **Language Support**: CouchDB uses JavaScript for map/reduce queries and views, providing flexibility and ease of use for developers, whereas Microsoft SQL Server primarily uses Transact-SQL (T-SQL) as its query language.
5. **Community and Licensing**: CouchDB is open-source and maintained by the Apache Software Foundation, making it freely accessible and adaptable, whereas Microsoft SQL Server is a proprietary software with licensing fees based on features and usage.

In Summary, the differences between CouchDB and Microsoft SQL Server lie in their data model, scalability, consistency, language support, and community/licensing. 

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Advice on Microsoft SQL Server, CouchDB

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
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
Josip
Josip

Senior frontend developer

Aug 31, 2021

Decided

Needed to transform intranet desktop application to the web-based one, as mid-term project. My choice was to use Django/Angular stack - Django since it, in conjunction with Python, enabled rapid development, an Angular since it was stable and enterprise-level framework. Deadlines were somewhat tight since the project to migrate was being developed for several years and had a lot of domain knowledge integrated into it. Definitely was good decision, since deadlines was manageable, juniors were able to enter the project very quickly and we were able to continuously deploy very well.

73.6k views73.6k
Comments

Detailed Comparison

Microsoft SQL Server
Microsoft SQL Server
CouchDB
CouchDB

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

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

-
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
Statistics
GitHub Stars
-
GitHub Stars
6.7K
GitHub Forks
-
GitHub Forks
1.1K
Stacks
21.3K
Stacks
529
Followers
15.5K
Followers
584
Votes
540
Votes
139
Pros & Cons
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
    The maximum number of connections is only 14000 connect
  • 1
    Replication can loose the data
  • 1
    Allwayon can loose data in asycronious mode
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency

What are some alternatives to Microsoft SQL Server, CouchDB?

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.

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.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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