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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cloud Storage
  5. CouchDB vs Google Cloud Storage

CouchDB vs Google Cloud Storage

OverviewDecisionsComparisonAlternatives

Overview

Google Cloud Storage
Google Cloud Storage
Stacks2.0K
Followers1.2K
Votes75
CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K

CouchDB vs Google Cloud Storage: What are the differences?

Developers describe CouchDB as "HTTP + JSON document database with Map Reduce views and peer-based replication". 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. On the other hand, Google Cloud Storage is detailed as "Durable and highly available object storage service". Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

CouchDB belongs to "Databases" category of the tech stack, while Google Cloud Storage can be primarily classified under "Cloud Storage".

"JSON" is the primary reason why developers consider CouchDB over the competitors, whereas "Scalable" was stated as the key factor in picking Google Cloud Storage.

CouchDB is an open source tool with 4.22K GitHub stars and 833 GitHub forks. Here's a link to CouchDB's open source repository on GitHub.

Evernote, Bugsnag, and Wix are some of the popular companies that use Google Cloud Storage, whereas CouchDB is used by Acadar, Third Iron, and SocialDecode. Google Cloud Storage has a broader approval, being mentioned in 179 company stacks & 74 developers stacks; compared to CouchDB, which is listed in 60 company stacks and 30 developer stacks.

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Advice on Google Cloud Storage, 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
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
Ben
Ben

May 18, 2020

Decided

We choose Backblaze B2 because it makes more sense for storing static assets.

We admire Backblaze's customer service & transparency, plus, we trust them to maintain fair business practices - including not raising prices in the future.

Lower storage costs means we can keep more data for longer, and lower bandwidth means cache misses don't cost a ton.

120k views120k
Comments

Detailed Comparison

Google Cloud Storage
Google Cloud Storage
CouchDB
CouchDB

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

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.

High Capacity and Scalability;Strong Data Consistency;Google Developers Console Projects;Bucket Locations;REST APIS;OAuth 2.0 Authentication;Authenticated Browser Downloads;Google Account Support for Sharing
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
2.0K
Stacks
529
Followers
1.2K
Followers
584
Votes
75
Votes
139
Pros & Cons
Pros
  • 28
    Scalable
  • 19
    Cheap
  • 14
    Reliable
  • 9
    Easy
  • 3
    Chealp
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency

What are some alternatives to Google Cloud Storage, 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.

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.

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