An introduction to MongoDB

We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. We aggregate information from all open source repositories. Search and find the best for your needs. Check out projects section.

An introduction to MongoDB

We aggregate and tag open source projects. We have collections of more than one million projects. Check out the projects section.

MongoDB is the most exciting SQL-free database currently available in the market. The new kid on the block, called MongoDB is a scalable, high-performance, open source, schema free and document oriented database that focuses on the ideas of NoSQL Approach. Written in C++, it has taken rapid strides since its emergence into the public sphere as a popular way to build your database applications.

The origin of MongoDB can be traced back to its original authors at 10gen, who developed MongoDB as a stand-alone product in 2009. With the introduction of MongoDB, the goal is to bridge the gap that exists between a key/value store and a traditional RDBMS. Its conception demanded eliminating the limitations of relational databases by changing the data model from relational to document-based. By doing that, it is able to add greater functionality with features such as, embedded docs for speed and manageability, and easier horizontal scalability as it is non-relational and does not support joins. Since MongoDB uses schema-less databases, it allows agile software development during the Software Development Life Cycle (SDLC). However, it has retained some highly functional features of MySQL as well, such as, indexes, dynamic queries and updates. Creating an index in MySql or Oracle and one in MongoDB is strikingly similar, except that in the case of latter, you have the option of indexing an embedded field.

What makes MongoDB such a great data store?

Document-oriented
The document-oriented nature of MongoDB is its major strength. It uses embedded documents and arrays, therefore multi-document transactions and joins are rarely used, which makes it highly scalable and efficient.

Scalability
Since document oriented architecture of MongoDB comprises of schema-less databases that rarely uses joins for queries, it renders horizontal scalability.

High performance
MongoDB is a high-performance SQL-free database. SQL and other relational database store relational data, for instance, data in table X can have direct relations to information in table Y. Since MongoDB doesn't need this ability, it functions without a lot of overhead, making it really fast. Add to that the fact that it is not yet ACID compliant helps its cause.

On the downside though, there are a few pressing issues which the community around the application need to focus on. The barrier to entry is relatively high when compared to SQL databases, as there is a lack of skillsets around NoSQL and its tools lack robustness of SQL. Also, as it is relatively new, it is hard to find NoSQL talent.

MongoDB is a great application when it comes to handling critical social interactions as in the case of social media network. Although, when you need to manage data where you have to guarantee data integrity, especially when financial transactions are involved, SQL is a far better choice. MongoDB works best with smaller datasets. Companies are using it for their research and data mining activities where the flexibility of MongoDB's document oriented architecture becomes easily evident. However, notwithstanding the downsides, the benefits justify the risks as is proven by its rapid adoption among IT professionals worldwide.


  Author: Jiji Thomas works as a content writer for Dataentryoutsourced. He also indulges in blogging, creative writing and photography.

Findbestopensource Editorial Team

We publish blog post about open source products. If you are interested in sharing knowledge about open source products, please visit write for us

Subscribe to our newsletter.

We will send mail once in a week about latest updates on open source tools and technologies. subscribe our newsletter

Connect to MongoDB and Perform CRUD using Java

MongoDB is a popular and widely used open source NoSQL database. MongoDB is a distributed database at its core, so high availability, horizontal scaling, and geographic distribution is quite possible. It is licensed under Server Side Public License. Recently they moved to Server Side Public License, before that MongoDB was released under AGPL. This article will provide basic example to connect and work with MongoDB using Java.

An Introduction to the UnQLite Embedded NoSQL Database Engine

UnQLite is an embedded NoSQL database engine. It's a standard Key/Value store similar to the more popular Berkeley DB and a document-store database similar to MongoDB with a built-in scripting language called Jx9 that looks like Javascript. Unlike most other NoSQL databases, UnQLite does not have a separate server process. UnQLite reads and writes directly to ordinary disk files. A complete database with multiple collections is contained in a single disk file. The database file format is cross-platform, you can freely copy a database between 32-bit and 64-bit systems or between big-endian and little-endian architectures.

Introduction to Apache Cassandra

Apache Cassandra was designed by Facebook and was open-sourced in July 2008. It is regarded as perfect choice when the users demand scalability and high availability without any impact towards performance. Apache Cassandra is highly scalable, high-performance distributed database designed to handle large voluminous amounts of data across many commodity servers with no failure.

Column database vs OLAP

OLAP (Online Analytical Processing), Reporting, Data mining related tasks are usually done by Business intelligence products. They do powerful Extraction, Transformation and Loading (ETL) the data and provides various reports. They use relational database as its back end. How could they generate better reports? Will column DB do a better job?

Lucene / Solr as NoSQL database

Lucene and Solr are most popular and widely used search engine. It indexes the content and delivers the search result faster. It has all capabilities of NoSQL database. This article describes about its pros and cons.

Best situation to use Column database

Column oriented database or datastore as the name sounds it stores the data by column rather than by row. It has some advantages and disadvantages over traditional RDBMS. Developer should know the typical situation to choose column oriented database.

Exonum Blockchain Framework by the Bitfury Group

Exonum is an extensible open source blockchain framework for building private blockchains which offers outstanding performance, data security, as well as fault tolerance. The framework does not include any business logic, instead, you can develop and add the services that meet your specific needs. Exonum can be used to build various solutions from a document registry to a DevOps facilitation system.

Light4j Cookbook - Rest API, CORS and RDBMS

Light 4j is a fast, lightweight and cloud-native microservices framework. In this article, we will see what and how hybrid framework works and integrate with RDMS databases like MySQL, also built in option of CORS handler for in-flight request.

LogicalDOC - Open Source DMS

LogicalDOC is both a document management and a collaboration system. The software is loaded with many functions and allows organizing, indexing, retrieving, controlling and distributing important business documents securely and safely for any organization and individual.

PySpark: Installation, RDDs, MLib, Broadcast and Accumulator

We knew that Apace Spark- the most famous parallel computing model or processing the massive data set is written in Scala programming language. The Apace foundation offered a tool to support the Python in Spark which was named PySpark. The PySpark allows us to use RDDs in Python programming language through a library called Py4j. This article provides basic introduction about PySpark, RDD, MLib, Broadcase and Accumulator.

Advantages and Disadvantages of using Hibernate like ORM libraries

Traditionally Programmers used ODBC, JDBC, ADO etc to access database. Developers need to write SQL queries, process the result set and convert the data in the form of objects (Data model). I think most programmers would typically write a function to convert the object to query and result set to object. To overcome these difficulties, ORM provides a mechanism to directly use objects and interact with the database.

An introduction to LucidWorks Enterprise Search

Lucidworks Enterprise search solution is built on top of Apache Solr. It scales seamlessly w/sub-second response times under extreme query loads for multi-billion document collections. It has user friendly UI, which does all the job of configuration and search.

Data dumping through REST API using Spring Batch

Most of the cloud services provide API to fetch their data. But data will be given as paginated results as returning the complete data will overshoot the response payload. To discover the complete list of books or e-courses or cloud machine details, we need to call the API page-wise till the end. In this scenario, we can use Spring Batch to get the data page by page and dump it into a file.

How Bitcoin works? A simple introduction.

Bitcoin is an open source digital currency which could be transferred in a P2P payment network. It is decentralized and it is not controlled by any central authority or banks. It is transferred from person to person and no authority will be aware of your transaction. Its quite different from PayPal or Banks.

Getting Started With Django Python Web Framework

Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. It is pre-loaded with user authentication, content administration, site maps, RSS feeds and many more tasks. Security features provided are cross site scripting (XSS) protection, cross site request forgery protection, SQL injection protection, click-jacking protection, host header validation, session security and so on. It also provides in built caching framework.

Desktop Apps using Electron JS with centralized data control

When there is a requirement for having local storage for the desktop application context and data needs to be synchronized to central database, we can think of Electron with PouchDB having CouchDB stack. Electron can be used for cross-platform desktop apps with pouch db as local storage. It can sync those data to centralized database CouchDB seamlessly so any point desktop apps can recover or persist the data. In this article, we will go through of creation of desktop apps with ElectronJS, PouchDB and show the sync happens seamlessly with remote CouchDB.

Apache OpenNLP - Document Classification

Apache OpenNLP is a library for natural language processing using machine learning. In this article, we will explore document/text classification by training with sample data and then execute to get its results. We will use plain training model as one example and then training using Navie Bayes Algorithm.

Rowy - Airtable-like simplicity for managing your Firestore data

Rowy an open-source platform to manage your data in an intuitive spreadsheet-like UI. Say goodbye to emailing that "vFinalFinal" Excel sheet. It helps to write Cloud Functions effortlessly in the browser, and connect to your favorite third party platforms such as SendGrid, Twilio, Algolia, Slack and more.

Cache using Hazelcast InMemory Data Grid

Hazelcast is an open source In-Memory Data Grid (IMDG). It provides elastically scalable distributed In-Memory computing, widely recognized as the fastest and most scalable approach to application performance. Hazelcast makes distributed computing simple by offering distributed implementations of many developer-friendly interfaces from Java such as Map, Queue, ExecutorService, Lock and JCache.

How to install and setup Redis

Redis is an open source (BSD licensed), in-memory data structure store, used also as a database cache and message broker. It is written in ANSI C and works in all the operating systems. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. This article explains about how to install Redis.