Cassandra vs CouchDB

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

Cassandra vs CouchDB: What are the differences?

Key Differences between Cassandra and CouchDB

Cassandra and CouchDB are both popular NoSQL databases with their own distinct features and use cases. Here are the key differences between these two databases:

Data Model: Cassandra follows a column-family data model, which means that data is stored in rows with columns grouped into column families. On the other hand, CouchDB uses a document-oriented data model where data is organized into JSON-like documents. This allows CouchDB to be more flexible in handling different types of data structures.
Scalability: Cassandra is designed for horizontal scalability and can easily handle large amounts of data across multiple nodes. It is known for its ability to scale linearly by adding more nodes to the cluster. CouchDB, on the other hand, is designed for single-node deployments and does not provide native support for distributed scaling.
Consistency: Cassandra offers tunable consistency, allowing users to choose between strong consistency and eventual consistency. It provides a highly available and fault-tolerant system with eventual consistency by default. In contrast, CouchDB offers strong consistency by default, ensuring that all replicas are updated before a write operation is considered successful.
Replication: Cassandra supports multiple replication strategies, including network topology and datacenter-aware replication, providing higher availability and fault tolerance. CouchDB, on the other hand, uses a peer-to-peer replication model, where each database can synchronize with multiple peers. This allows for offline operations and decentralized architecture.
Querying: Cassandra uses CQL (Cassandra Query Language) for querying data, which is similar to SQL but with some additional features. It supports a wide range of query capabilities, including filtering, sorting, and indexing. CouchDB uses MapReduce for querying data, allowing users to define custom Map and Reduce functions to process and aggregate data.
Conflict Resolution: In case of conflicts during concurrent updates, Cassandra uses last-write-wins conflict resolution, where the latest write operation overwrites the previous conflicting values. CouchDB, on the other hand, uses an MVCC (Multi-Version Concurrency Control) approach for conflict resolution, preserving all versions of a document and allowing users to manually resolve conflicts.

In Summary, Cassandra and CouchDB have different data models, scalability approaches, consistency levels, replication strategies, querying methods, and conflict resolution mechanisms. The choice between these databases depends on specific use cases and requirements.

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Advice on Cassandra, CouchDB

Micha

CEO & Co-Founder at Dechea

May 27, 2022

Decided

Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.

Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.

93k views93k

Comments

Gabriel

CEO at Naologic

Jan 2, 2020

Decidedon

CouchDB

Couchbase

Memcached

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

Krishna Chaitanya

Head of Technology at Adonmo

Jun 27, 2021

Review

For such a more realtime-focused, data-centered application like an exchange, it's not the frontend or backend that matter much. In fact for that, they can do away with any of the popular frameworks like React/Vue/Angular for the frontend and Go/Python for the backend. For example uniswap's frontend (although much simpler than binance) is built in React. The main interesting part here would be how they are able to handle updating data so quickly. In my opinion, they might be heavily reliant on realtime processing systems like Kafka+Kafka Streams, Apache Flink or Apache Spark Stream or similar. For more processing heavy but not so real-time processing, they might be relying on OLAP and/or warehousing tools like Cassandra/Redshift. They could have also optimized few high frequent queries using NoSQL stores like mongodb (for persistance) and in-memory cache like Redis (for further perfomance boost to get millisecond latencies).

53.8k views53.8k

Comments

Detailed Comparison

Cassandra	CouchDB
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.	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 9.5K	GitHub Stars 6.7K
GitHub Forks 3.8K	GitHub Forks 1.1K
Stacks 3.6K	Stacks 529
Followers 3.5K	Followers 584
Votes 507	Votes 139
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Updates 1 Size	Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency

What are some alternatives to Cassandra, CouchDB?

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

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

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.

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

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 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

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 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.

Related Comparisons

Cassandra vs CouchDB: What are the differences?

Key Differences between Cassandra and CouchDB

Cassandra and CouchDB are both popular NoSQL databases with their own distinct features and use cases. Here are the key differences between these two databases:

Data Model: Cassandra follows a column-family data model, which means that data is stored in rows with columns grouped into column families. On the other hand, CouchDB uses a document-oriented data model where data is organized into JSON-like documents. This allows CouchDB to be more flexible in handling different types of data structures.
Scalability: Cassandra is designed for horizontal scalability and can easily handle large amounts of data across multiple nodes. It is known for its ability to scale linearly by adding more nodes to the cluster. CouchDB, on the other hand, is designed for single-node deployments and does not provide native support for distributed scaling.
Consistency: Cassandra offers tunable consistency, allowing users to choose between strong consistency and eventual consistency. It provides a highly available and fault-tolerant system with eventual consistency by default. In contrast, CouchDB offers strong consistency by default, ensuring that all replicas are updated before a write operation is considered successful.
Replication: Cassandra supports multiple replication strategies, including network topology and datacenter-aware replication, providing higher availability and fault tolerance. CouchDB, on the other hand, uses a peer-to-peer replication model, where each database can synchronize with multiple peers. This allows for offline operations and decentralized architecture.
Querying: Cassandra uses CQL (Cassandra Query Language) for querying data, which is similar to SQL but with some additional features. It supports a wide range of query capabilities, including filtering, sorting, and indexing. CouchDB uses MapReduce for querying data, allowing users to define custom Map and Reduce functions to process and aggregate data.
Conflict Resolution: In case of conflicts during concurrent updates, Cassandra uses last-write-wins conflict resolution, where the latest write operation overwrites the previous conflicting values. CouchDB, on the other hand, uses an MVCC (Multi-Version Concurrency Control) approach for conflict resolution, preserving all versions of a document and allowing users to manually resolve conflicts.

Cassandra vs CouchDB

Overview

Cassandra vs CouchDB: What are the differences?