CouchDB vs Event Store

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

Event Store

Stacks69

Followers82

Votes1

CouchDB vs Event Store: 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, Event Store is detailed as "*The open-source, functional database with Complex Event Processing *". It stores your data as a series of immutable events over time, making it easy to build event-sourced applications. It can run as a cluster of nodes containing the same data, which remains available for writes provided at least half the nodes are alive and connected.

CouchDB and Event Store belong to "Databases" category of the tech stack.

CouchDB is an open source tool with 4.26K GitHub stars and 844 GitHub forks. Here's a link to CouchDB's open source repository on GitHub.

According to the StackShare community, CouchDB has a broader approval, being mentioned in 76 company stacks & 196 developers stacks; compared to Event Store, which is listed in 9 company stacks and 11 developer stacks.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on CouchDB, Event Store

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

Detailed Comparison

CouchDB	Event Store
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 stores your data as a series of immutable events over time, making it easy to build event-sourced applications. It can run as a cluster of nodes containing the same data, which remains available for writes provided at least half the nodes are alive and connected.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	Guaranteed writes; High availability; Projections; Multiple client interfaces; Optimistic concurrency checks; Subscribe to streams with competing consumers; Great performance that scales; Multiple hosting options; Commercial support plans; Immutable data store; Atom subscriptions
Statistics
GitHub Stars 6.7K	GitHub Stars -
GitHub Forks 1.1K	GitHub Forks -
Stacks 529	Stacks 69
Followers 584	Followers 82
Votes 139	Votes 1
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Pros 1 Trail Log
Integrations
No integrations available	.NET SQLite MySQL

What are some alternatives to CouchDB, Event Store?

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.

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 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.