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  5. CouchDB vs Google Cloud Spanner

CouchDB vs Google Cloud Spanner

OverviewDecisionsComparisonAlternatives

Overview

CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

CouchDB vs Google Cloud Spanner: What are the differences?

## Introduction

Key differences between CouchDB and Google Cloud Spanner are outlined below:

1. **Data Model**: CouchDB uses a flexible schemaless document model allowing for easy storing of structured and unstructured data. In contrast, Google Cloud Spanner uses a relational data model, which enforces schema with strong consistency for ACID transactions.
2. **Scalability**: CouchDB is designed for horizontal scalability with built-in support for multiple-node clustering. On the other hand, Google Cloud Spanner provides horizontal scalability through its globally distributed architecture, allowing for scaling to petabytes of data across regions.
3. **Consistency Model**: CouchDB offers eventual consistency by default, allowing for high availability and partition tolerance in a distributed environment. In contrast, Google Cloud Spanner provides strong consistency across globally distributed data using its TrueTime API, ensuring data synchronization and correctness.
4. **Query Language**: CouchDB uses MapReduce for querying, which requires writing custom map and reduce functions in JavaScript. Google Cloud Spanner uses SQL for querying data, providing a familiar and efficient way to retrieve and manipulate data stored in the database.
5. **Transaction Support**: CouchDB supports multi-document transactions within a single database instance. Google Cloud Spanner, on the other hand, provides distributed transactions across multiple databases and geographically distributed regions, ensuring data integrity and atomicity.
6. **Pricing Model**: CouchDB is open-source and free to use, with support for on-premises installations. Google Cloud Spanner is a managed database service on Google Cloud Platform, offering tiered pricing based on usage, storage, and network egress.

In Summary, CouchDB and Google Cloud Spanner differ in their data model, scalability, consistency model, query language, transaction support, and pricing model, making them suitable for different use cases based on specific requirements.

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Advice on CouchDB, Google Cloud Spanner

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

Detailed Comparison

CouchDB
CouchDB
Google Cloud Spanner
Google Cloud Spanner

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.

It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.

Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
6.7K
GitHub Stars
2.0K
GitHub Forks
1.1K
GitHub Forks
1.1K
Stacks
529
Stacks
57
Followers
584
Followers
117
Votes
139
Votes
3
Pros & Cons
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
No integrations available
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to CouchDB, Google Cloud Spanner?

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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