Alternatives to LokiJS logo

Alternatives to LokiJS

Redis, SQLite, Pouchdb, NeDB, and MongoDB are the most popular alternatives and competitors to LokiJS.
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What is LokiJS and what are its top alternatives?

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.
LokiJS is a tool in the In-Memory Databases category of a tech stack.
LokiJS is an open source tool with 6K GitHub stars and 466 GitHub forks. Here’s a link to LokiJS's open source repository on GitHub

Top Alternatives to LokiJS

  • Redis

    Redis

    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. ...

  • 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. ...

  • Pouchdb

    Pouchdb

    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. ...

  • NeDB

    NeDB

    Embedded persistent or in memory database for Node.js, nw.js, Electron and browsers, 100% JavaScript, no binary dependency. API is a subset of MongoDB's and it's plenty fast. ...

  • 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. ...

  • IndexedDB

    IndexedDB

    This API uses indexes to enable high-performance searches of this data. While Web Storage is useful for storing smaller amounts of data, it is less useful for storing larger amounts of structured data. ...

  • AlaSQL

    AlaSQL

    Open source SQL database for Javascript with a strong focus on query speed and datasource flexibility for relational data, schemaless data, and graph data. Works in your browser, Node.js and Cordova. Handles both traditional relational tables and nested JSON data (NoSQL). Export, store, and import data from localStorage, IndexedDB, and Excel. ...

  • Hazelcast

    Hazelcast

    With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution. ...

LokiJS alternatives & related posts

Redis logo

Redis

43.4K
32.4K
3.9K
An in-memory database that persists on disk
43.4K
32.4K
+ 1
3.9K
PROS OF REDIS
  • 875
    Performance
  • 535
    Super fast
  • 511
    Ease of use
  • 441
    In-memory cache
  • 321
    Advanced key-value cache
  • 190
    Open source
  • 179
    Easy to deploy
  • 163
    Stable
  • 153
    Free
  • 120
    Fast
  • 40
    High-Performance
  • 39
    High Availability
  • 34
    Data Structures
  • 32
    Very Scalable
  • 23
    Replication
  • 20
    Great community
  • 19
    Pub/Sub
  • 17
    "NoSQL" key-value data store
  • 14
    Hashes
  • 12
    Sets
  • 10
    Sorted Sets
  • 9
    Lists
  • 8
    BSD licensed
  • 8
    NoSQL
  • 7
    Async replication
  • 7
    Integrates super easy with Sidekiq for Rails background
  • 7
    Bitmaps
  • 6
    Open Source
  • 6
    Keys with a limited time-to-live
  • 5
    Strings
  • 5
    Lua scripting
  • 4
    Awesomeness for Free!
  • 4
    Hyperloglogs
  • 3
    outstanding performance
  • 3
    Runs server side LUA
  • 3
    Networked
  • 3
    LRU eviction of keys
  • 3
    Written in ANSI C
  • 3
    Feature Rich
  • 3
    Transactions
  • 2
    Data structure server
  • 2
    Performance & ease of use
  • 1
    Existing Laravel Integration
  • 1
    Automatic failover
  • 1
    Easy to use
  • 1
    Object [key/value] size each 500 MB
  • 1
    Simple
  • 1
    Channels concept
  • 1
    Scalable
  • 1
    Temporarily kept on disk
  • 1
    Dont save data if no subscribers are found
  • 0
    Jk
CONS OF REDIS
  • 14
    Cannot query objects directly
  • 2
    No secondary indexes for non-numeric data types
  • 1
    No WAL

related Redis posts

Robert Zuber

We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

See more

I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

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SQLite logo

SQLite

12.4K
9.7K
528
A software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine
12.4K
9.7K
+ 1
528
PROS OF SQLITE
  • 160
    Lightweight
  • 134
    Portable
  • 121
    Simple
  • 80
    Sql
  • 28
    Preinstalled on iOS and Android
  • 2
    Tcl integration
  • 1
    Free
  • 1
    Telefon
  • 1
    Portable A database on my USB 'love it'
CONS OF SQLITE
  • 2
    Not for multi-process of multithreaded apps
  • 1
    Needs different binaries for each platform

related SQLite posts

Dimelo Waterson
Shared insights
on
PostgreSQLPostgreSQLMySQLMySQLSQLiteSQLite

I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

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Christian Stefanescu
Head of IT at lawpilots · | 3 upvotes · 11.6K views
Shared insights
on
DjangoDjangoSQLiteSQLitePostgreSQLPostgreSQL

While I love and use PostgreSQL , I would definitely recommend having a look at SQLite as well. It can be a solid database for lots of applications and it brings some advantages in terms of handling: you don't need a server running, which makes things like testing, deploying or backing up databases much easier. Through the ORM in Django you are one abstraction level away from your database anyway and switching later on is definitely an option, but I believe SQLite is very good for pretty much all the small applications you can think of.

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Pouchdb logo

Pouchdb

110
201
5
Open-source JavaScript database inspired by Apache CouchDB that's designed to run well within the browser
110
201
+ 1
5
PROS OF POUCHDB
  • 1
    Offline cache
  • 1
    Very fast
  • 1
    JSON
  • 1
    Free
  • 1
    Repication
CONS OF POUCHDB
    Be the first to leave a con

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    Jonathan Pugh
    Software Engineer / Project Manager / Technical Architect · | 25 upvotes · 1.6M views

    I needed to choose a full stack of tools for cross platform mobile application design & development. After much research and trying different tools, these are what I came up with that work for me today:

    For the client coding I chose Framework7 because of its performance, easy learning curve, and very well designed, beautiful UI widgets. I think it's perfect for solo development or small teams. I didn't like React Native. It felt heavy to me and rigid. Framework7 allows the use of #CSS3, which I think is the best technology to come out of the #WWW movement. No other tech has been able to allow designers and developers to develop such flexible, high performance, customisable user interface elements that are highly responsive and hardware accelerated before. Now #CSS3 includes variables and flexboxes it is truly a powerful language and there is no longer a need for preprocessors such as #SCSS / #Sass / #less. React Native contains a very limited interpretation of #CSS3 which I found very frustrating after using #CSS3 for some years already and knowing its powerful features. The other very nice feature of Framework7 is that you can even build for the browser if you want your app to be available for desktop web browsers. The latest release also includes the ability to build for #Electron so you can have MacOS, Windows and Linux desktop apps. This is not possible with React Native yet.

    Framework7 runs on top of Apache Cordova. Cordova and webviews have been slated as being slow in the past. Having a game developer background I found the tweeks to make it run as smooth as silk. One of those tweeks is to use WKWebView. Another important one was using srcset on images.

    I use #Template7 for the for the templating system which is a no-nonsense mobile-centric #HandleBars style extensible templating system. It's easy to write custom helpers for, is fast and has a small footprint. I'm not forced into a new paradigm or learning some new syntax. It operates with standard JavaScript, HTML5 and CSS 3. It's written by the developer of Framework7 and so dovetails with it as expected.

    I configured TypeScript to work with the latest version of Framework7. I consider TypeScript to be one of the best creations to come out of Microsoft in some time. They must have an amazing team working on it. It's very powerful and flexible. It helps you catch a lot of bugs and also provides code completion in supporting IDEs. So for my IDE I use Visual Studio Code which is a blazingly fast and silky smooth editor that integrates seamlessly with TypeScript for the ultimate type checking setup (both products are produced by Microsoft).

    I use Webpack and Babel to compile the JavaScript. TypeScript can compile to JavaScript directly but Babel offers a few more options and polyfills so you can use the latest (and even prerelease) JavaScript features today and compile to be backwards compatible with virtually any browser. My favorite recent addition is "optional chaining" which greatly simplifies and increases readability of a number of sections of my code dealing with getting and setting data in nested objects.

    I use some Ruby scripts to process images with ImageMagick and pngquant to optimise for size and even auto insert responsive image code into the HTML5. Ruby is the ultimate cross platform scripting language. Even as your scripts become large, Ruby allows you to refactor your code easily and make it Object Oriented if necessary. I find it the quickest and easiest way to maintain certain aspects of my build process.

    For the user interface design and prototyping I use Figma. Figma has an almost identical user interface to #Sketch but has the added advantage of being cross platform (MacOS and Windows). Its real-time collaboration features are outstanding and I use them a often as I work mostly on remote projects. Clients can collaborate in real-time and see changes I make as I make them. The clickable prototyping features in Figma are also very well designed and mean I can send clickable prototypes to clients to try user interface updates as they are made and get immediate feedback. I'm currently also evaluating the latest version of #AdobeXD as an alternative to Figma as it has the very cool auto-animate feature. It doesn't have real-time collaboration yet, but I heard it is proposed for 2019.

    For the UI icons I use Font Awesome Pro. They have the largest selection and best looking icons you can find on the internet with several variations in styles so you can find most of the icons you want for standard projects.

    For the backend I was using the #GraphCool Framework. As I later found out, #GraphQL still has some way to go in order to provide the full power of a mature graph query language so later in my project I ripped out #GraphCool and replaced it with CouchDB and Pouchdb. Primarily so I could provide good offline app support. CouchDB with Pouchdb is very flexible and efficient combination and overcomes some of the restrictions I found in #GraphQL and hence #GraphCool also. The most impressive and important feature of CouchDB is its replication. You can configure it in various ways for backups, fault tolerance, caching or conditional merging of databases. CouchDB and Pouchdb even supports storing, retrieving and serving binary or image data or other mime types. This removes a level of complexity usually present in database implementations where binary or image data is usually referenced through an #HTML5 link. With CouchDB and Pouchdb apps can operate offline and sync later, very efficiently, when the network connection is good.

    I use PhoneGap when testing the app. It auto-reloads your app when its code is changed and you can also install it on Android phones to preview your app instantly. iOS is a bit more tricky cause of Apple's policies so it's not available on the App Store, but you can build it and install it yourself to your device.

    So that's my latest mobile stack. What tools do you use? Have you tried these ones?

    See more
    Mike Endale
    Shared insights
    on
    Android SDKAndroid SDKRealmRealmPouchdbPouchdb
    at

    We are building an offline-first Android SDK app. The solution we're working on runs on a mobile device in areas where internet connectivity is intermittent or does not exist. The applications needs to be able to collect data and when it reaches a home base or finds internet connectivity, we'll sync it with the host.

    We've heard Realm and Pouchdb could be a good solution, but we are curious if anyone has any experience with either or have another path forward.

    See more
    NeDB logo

    NeDB

    25
    67
    0
    Simple in-app or in-browser pure javascript database
    25
    67
    + 1
    0
    PROS OF NEDB
      Be the first to leave a pro
      CONS OF NEDB
        Be the first to leave a con

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        MongoDB logo

        MongoDB

        65K
        54.2K
        4.1K
        The database for giant ideas
        65K
        54.2K
        + 1
        4.1K
        PROS OF MONGODB
        • 824
          Document-oriented storage
        • 591
          No sql
        • 546
          Ease of use
        • 465
          Fast
        • 406
          High performance
        • 256
          Free
        • 215
          Open source
        • 179
          Flexible
        • 142
          Replication & high availability
        • 109
          Easy to maintain
        • 41
          Querying
        • 37
          Easy scalability
        • 36
          Auto-sharding
        • 35
          High availability
        • 31
          Map/reduce
        • 26
          Document database
        • 24
          Easy setup
        • 24
          Full index support
        • 15
          Reliable
        • 14
          Fast in-place updates
        • 13
          Agile programming, flexible, fast
        • 11
          No database migrations
        • 7
          Easy integration with Node.Js
        • 7
          Enterprise
        • 5
          Enterprise Support
        • 4
          Great NoSQL DB
        • 3
          Aggregation Framework
        • 3
          Support for many languages through different drivers
        • 3
          Drivers support is good
        • 2
          Schemaless
        • 2
          Easy to Scale
        • 2
          Fast
        • 2
          Awesome
        • 2
          Managed service
        • 1
          Consistent
        CONS OF MONGODB
        • 5
          Very slowly for connected models that require joins
        • 3
          Not acid compliant
        • 1
          Proprietary query language

        related MongoDB posts

        Jeyabalaji Subramanian

        Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

        We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

        Based on the above criteria, we selected the following tools to perform the end to end data replication:

        We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

        We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

        In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

        Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

        In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

        See more
        Robert Zuber

        We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

        As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

        When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

        See more
        IndexedDB logo

        IndexedDB

        27
        62
        0
        A low-level API for client-side storage of significant amounts of structured data
        27
        62
        + 1
        0
        PROS OF INDEXEDDB
          Be the first to leave a pro
          CONS OF INDEXEDDB
            Be the first to leave a con

            related IndexedDB posts

            AlaSQL logo

            AlaSQL

            25
            27
            0
            JavaScript SQL Database for Browser and Node.js
            25
            27
            + 1
            0
            PROS OF ALASQL
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              CONS OF ALASQL
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                Hazelcast logo

                Hazelcast

                243
                366
                56
                Clustering and highly scalable data distribution platform for Java
                243
                366
                + 1
                56
                PROS OF HAZELCAST
                • 10
                  High Availibility
                • 6
                  Distributed Locking
                • 5
                  Distributed compute
                • 5
                  Sharding
                • 4
                  Load balancing
                • 3
                  Sql query support in cluster wide
                • 3
                  Map-reduce functionality
                • 3
                  Written in java. runs on jvm
                • 3
                  Publish-subscribe
                • 2
                  Performance
                • 2
                  Simple-to-use
                • 2
                  Multiple client language support
                • 2
                  Rest interface
                • 2
                  Optimis locking for map
                • 1
                  Super Fast
                • 1
                  Admin Interface (Management Center)
                • 1
                  Better Documentation
                • 1
                  Easy to use
                CONS OF HAZELCAST
                • 3
                  License needed for SSL

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