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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Pouchdb vs RocksDB

Pouchdb vs RocksDB

OverviewComparisonAlternatives

Overview

RocksDB
RocksDB
Stacks141
Followers290
Votes11
GitHub Stars30.9K
Forks6.6K
Pouchdb
Pouchdb
Stacks148
Followers242
Votes6
GitHub Stars17.5K
Forks1.5K

Pouchdb vs RocksDB: What are the differences?

Introduction:
PouchDB and RocksDB are two popular open-source database systems that are widely used in different applications. While both serve the purpose of data storage, they have key differences that make them suitable for different use cases. 

1. **Data Structure**: PouchDB is a document-oriented database that stores data in JSON format, making it easy to work with complex hierarchical data structures. On the other hand, RocksDB is a key-value store that does not provide the high-level abstractions of documents but offers efficient storage for key-value pairs.

2. **Browser vs. Server**: PouchDB is designed to run in the browser environment, allowing developers to work seamlessly with local data in web applications. RocksDB, on the other hand, is more suited for server-side applications where high performance and scalability are key requirements.

3. **Synchronization**: PouchDB comes with built-in synchronization capabilities, enabling seamless replication of data between multiple devices and servers. RocksDB, on the other hand, does not provide native synchronization features and requires additional components to achieve data replication.

4. **Concurrency Control**: RocksDB is optimized for concurrent read and write operations, making it a suitable choice for high-throughput applications that require efficient data access. PouchDB, while offering concurrency support, may not be as performant as RocksDB in scenarios with high levels of simultaneous data modifications.

5. **Programming Language Support**: PouchDB is primarily built using JavaScript and can be seamlessly integrated into Node.js and browser applications. RocksDB, on the other hand, is written in C++ and provides bindings for various programming languages, making it a versatile choice for developers working in different environments.

In Summary, PouchDB and RocksDB differ in terms of data structure, environment compatibility, synchronization capabilities, concurrency control, and programming language support, catering to distinct use cases in the realm of database systems. 

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Detailed Comparison

RocksDB
RocksDB
Pouchdb
Pouchdb

RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.

Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Cross browser compatibility; Lightweight; Easy to learn; Open source
Statistics
GitHub Stars
30.9K
GitHub Stars
17.5K
GitHub Forks
6.6K
GitHub Forks
1.5K
Stacks
141
Stacks
148
Followers
290
Followers
242
Votes
11
Votes
6
Pros & Cons
Pros
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed
Pros
  • 2
    Offline cache
  • 1
    Very fast
  • 1
    Free
  • 1
    Repication
  • 1
    JSON

What are some alternatives to RocksDB, Pouchdb?

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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