Apache Flink vs CouchDB

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

Apache Flink

Stacks534

Followers879

Votes38

GitHub Stars25.4K

Forks13.7K

CouchDB vs Apache Flink: 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, Apache Flink is detailed as "Fast and reliable large-scale data processing engine". Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

CouchDB belongs to "Databases" category of the tech stack, while Apache Flink can be primarily classified under "Big Data Tools".

"JSON" is the primary reason why developers consider CouchDB over the competitors, whereas "Unified batch and stream processing" was stated as the key factor in picking Apache Flink.

CouchDB and Apache Flink are both open source tools. Apache Flink with 9.36K GitHub stars and 5.01K forks on GitHub appears to be more popular than CouchDB with 4.24K GitHub stars and 835 GitHub forks.

BrightMachine, Bit Zesty, and Meltwater are some of the popular companies that use CouchDB, whereas Apache Flink is used by Zalando, sovrn Holdings, and BetterCloud. CouchDB has a broader approval, being mentioned in 61 company stacks & 32 developers stacks; compared to Apache Flink, which is listed in 20 company stacks and 22 developer stacks.

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Advice on CouchDB, Apache Flink

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

Nilesh

Technical Architect at Self Employed

Jul 8, 2020

Needs adviceon

Elasticsearch

Kafka

We have a Kafka topic having events of type A and type B. We need to perform an inner join on both type of events using some common field (primary-key). The joined events to be inserted in Elasticsearch.

In usual cases, type A and type B events (with same key) observed to be close upto 15 minutes. But in some cases they may be far from each other, lets say 6 hours. Sometimes event of either of the types never come.

In all cases, we should be able to find joined events instantly after they are joined and not-joined events within 15 minutes.

576k views576k

Comments

Detailed Comparison

CouchDB	Apache Flink
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.	Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	Hybrid batch/streaming runtime that supports batch processing and data streaming programs.;Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.;Flexible and expressive windowing semantics for data stream programs;Built-in program optimizer that chooses the proper runtime operations for each program;Custom type analysis and serialization stack for high performance
Statistics
GitHub Stars 6.7K	GitHub Stars 25.4K
GitHub Forks 1.1K	GitHub Forks 13.7K
Stacks 529	Stacks 534
Followers 584	Followers 879
Votes 139	Votes 38
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Pros 16 Unified batch and stream processing 8 Easy to use streaming apis 8 Out-of-the box connector to kinesis,s3,hdfs 4 Open Source 2 Low latency
Integrations
No integrations available	YARN Hadoop Hadoop HBase Kafka

What are some alternatives to CouchDB, Apache Flink?

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.

Related Comparisons

"JSON" is the primary reason why developers consider CouchDB over the competitors, whereas "Unified batch and stream processing" was stated as the key factor in picking Apache Flink.

Apache Flink vs CouchDB