LokiJS vs Pouchdb

Overview

Pouchdb

Stacks148

Followers242

Votes6

GitHub Stars17.5K

Forks1.5K

LokiJS

Stacks43

Followers57

Votes3

GitHub Stars6.8K

Forks483

LokiJS vs Pouchdb: What are the differences?

<Write Introduction here>

Data Structure: LokiJS is an in-memory database that stores data in collections, while PouchDB is a document-oriented database that stores data in JSON format in documents.
Synchronization: PouchDB supports synchronization with remote databases like CouchDB and IBM Cloudant, allowing for seamless data replication across different devices and platforms. In contrast, LokiJS does not provide built-in synchronization capabilities with remote databases.
Backend Support: PouchDB can utilize various backend storage solutions such as IndexedDB, WebSQL, and LevelDB based on the environment, providing flexibility in data persistence. On the other hand, LokiJS primarily focuses on saving data in memory or to disk using a custom persistence adapter.
Querying: LokiJS offers a powerful querying mechanism with support for indexes and dynamic views, enabling efficient data retrieval operations. In comparison, PouchDB's querying capabilities are more limited, primarily relying on MapReduce functions for data manipulation.
Community and Ecosystem: PouchDB has a larger and more active community, resulting in better support, frequent updates, and a wider range of plugins and integrations available for developers. LokiJS, while still actively maintained, lacks the extensive ecosystem that PouchDB possesses.
Usage Scenarios: Due to their inherent differences in data structure and synchronization capabilities, LokiJS is more suitable for applications requiring fast in-memory data operations, while PouchDB is better suited for projects that require seamless data synchronization across multiple devices or platforms.

In Summary, LokiJS and PouchDB differ in data structure, synchronization, backend support, querying capabilities, community size, and ideal usage scenarios.

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CLI (Node.js)

Manual

Detailed Comparison

Pouchdb	LokiJS
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.	LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.
Cross browser compatibility; Lightweight; Easy to learn; Open source	-
Statistics
GitHub Stars 17.5K	GitHub Stars 6.8K
GitHub Forks 1.5K	GitHub Forks 483
Stacks 148	Stacks 43
Followers 242	Followers 57
Votes 6	Votes 3
Pros & Cons
Pros 2 Offline cache 1 Very fast 1 Free 1 Repication 1 JSON	Pros 3 Can query the objects directly
Integrations
No integrations available	Node.js NativeScript Apache Cordova PhoneGap

What are some alternatives to Pouchdb, LokiJS?

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.

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

Related Comparisons

LokiJS vs Pouchdb: What are the differences?

<Write Introduction here>

Data Structure: LokiJS is an in-memory database that stores data in collections, while PouchDB is a document-oriented database that stores data in JSON format in documents.
Synchronization: PouchDB supports synchronization with remote databases like CouchDB and IBM Cloudant, allowing for seamless data replication across different devices and platforms. In contrast, LokiJS does not provide built-in synchronization capabilities with remote databases.
Backend Support: PouchDB can utilize various backend storage solutions such as IndexedDB, WebSQL, and LevelDB based on the environment, providing flexibility in data persistence. On the other hand, LokiJS primarily focuses on saving data in memory or to disk using a custom persistence adapter.
Querying: LokiJS offers a powerful querying mechanism with support for indexes and dynamic views, enabling efficient data retrieval operations. In comparison, PouchDB's querying capabilities are more limited, primarily relying on MapReduce functions for data manipulation.
Community and Ecosystem: PouchDB has a larger and more active community, resulting in better support, frequent updates, and a wider range of plugins and integrations available for developers. LokiJS, while still actively maintained, lacks the extensive ecosystem that PouchDB possesses.
Usage Scenarios: Due to their inherent differences in data structure and synchronization capabilities, LokiJS is more suitable for applications requiring fast in-memory data operations, while PouchDB is better suited for projects that require seamless data synchronization across multiple devices or platforms.

In Summary, LokiJS and PouchDB differ in data structure, synchronization, backend support, querying capabilities, community size, and ideal usage scenarios.

LokiJS vs Pouchdb

Overview