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The Salient Features of MongoDB That Makes It So Popular in 2019

MongoDB Database is a document-oriented database & NoSQL database. The Salient Features of MongoDB Database That Makes It So Popular in 2019.

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The Salient Features of MongoDB

The phenomenon of increasing data all over the world has been of significant interest and so organizations and businesses are looking for novel and more efficient techniques of managing the gigantic flood of data. They are more and more attracted by the alternate database management applications and tools as opposed to the traditional or the conventional relational database systems. MongoDB is one such cutting-edge and useful unconventional database management system.

What is MongoDB?

According to https://intellipaat.com, Mongo DB could be defined as an effective open-source database which utilizes a document-based data model along with a popular non-structured query language. MongoDB is supposed to be a powerful and competent NoSQL system that is stealing the show today in the global database software market. Here are some of the striking features of Mongo DB.

Salient Features of MongoDB Database

Ad-Hoc Queries

Usually, while designing a database’s schema, you would not know in advance the queries that would be performed. You must know in this context, ad-hoc queries are queries that are unknown at the time of structuring the database. Hence, we find that MongoDB is effective in providing solid ad-hoc queries support that makes it really more special. Ad-hoc queries actually seem to be updated very much in real time, culminating in enhancements and boosts in performance.

Schema-Less Database

In the case of Mongo DB, we understand that one collection would be holding different documents. MongoDB has absolutely no schema hence; it could be having numerous fields, size, and content differing from another document belonging to the same collection. MongoDB is known to demonstrate flexibility while dealing with and effectively handing the databases. You may seek the expert services of RemoteDBA.com for the perfect solution.

Document-Based

MongoDB is actually a document-based database that is an amazing characteristic in itself. We know that in the case of the relational databases, you would be finding rows and tables for data arrangement. Each and every row would be having a specific number of columns. These columns are known for storing a precise kind of data. However, in the case of NoSQL the rows and tables are substituted with fields. There seem to be different documents that could be storing diverse types of data. We understand that there are collections or groups of similar documents. Every document is supposed to be having a key ID that is unique or even a unique object ID that could both be user or system-defined.

Indexing Out of the Box

Indexes are used to optimize search performance. MongoDB allows any field in a standard document to be indexed using primary and secondary indexes. This ability to resolve queries rapidly and efficiently is among the best features of the platform and has earned it a lot of praise from the developer community. MongoDB’s database engine uses a predefined index which maps fields and can be used to find documents that are compatible with a particular query, thus vastly improving performance. This becomes even more evident if a document is queried repeatedly- you will certainly appreciate the speed boost.

Replication and Redundancy

MongoDB uses replication to achieve redundancy. This essentially means that the data for the application is distributed across multiple machines. Essentially, there will be a set of primary nodes, and one or multiple sets of replica nodes. Replication is extremely important for contingency management. Replica sets follow the principle of master-slave replication, which means there is a master node, which can perform read and write activities, while the slave nodes can only copy the data from a corresponding master node (read-only) without changing its values.

MongoDB replica sets also feature something called the automatic failover. In case the primary node is down for over 10 seconds or fails an integrity check, the system can consider a secondary instance to be the new primary. This allows uninterrupted, smooth operation and also saves a considerable amount of time that would have gone into maintenance and data recovery. When the previous primary node is back online, it will enter the pool as a second instance to be elected in the future by the replica set. This high-availability low-downtime model is the key to production-ready systems that MongoDB is deployed in.

Aggregation

MongoDB is supposed to have an integration framework that is great for efficient usability. You could be successfully batching process data and getting a single outcome even after performing diverse operations on the group or collection data. We know that the map-reduce function, single-purpose aggregation, and the aggregation pipeline methods are supposed to be three effective ways of providing an aggregation framework.

GridFS

A striking feature of both storing and even retrieving files is called GridFS. For files over 16 MB, this specific feature is supposed to be quite useful. GridFS would be effectively dividing a particular document into parts referred to as chunks and storing them properly in another separate document. The default size of all these chunks barring the last chunk would be 255 KB.

Sharding

While dealing with bigger datasets, sharding as a concept is introduced. This humungous data could result in some issues in case a query comes regarding them. Sharding is a striking feature that would be assisting in the distribution of this problematic data among multiple MongoDB instances. The collections found in MongoDB that has a relatively bigger size are actually distributed in several collections. All these collections are referred to as shards and they are actually implemented by clusters.

High Performance

MongoDB is supposed to be a competent open source database that offers high performance. This demonstrates scalability and high availability. It would be having really faster query response simply because of replication and indexing. This would be the reason why MongoDB must be regarded as the right choice for real-time and big data applications.

MongoDB Management Service

MMS is a robust web tool for effective database tracking and even for backing up your data. We are told that MMS is also tracking hardware metrics to effectively manage a MongoDB deployment. It would be demonstrating performance in a fully-featured web console for assisting you in optimizing your deployment. It would also, be providing characteristics such as custom alerts that should help you in discovering issues much before your MongoDB instance would be impacted.

Conclusion

We have mentioned some of the important features and characteristics of MongoDB such as Sharding, High Performance, Aggregation, Ad-Hoc Queries, Indexing, Replication, and Schema-Less database, GridFS, etc. You must know the advantages and disadvantages associated with MongoDB.

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Software

The Rise And Risk Of Third Party Code

Third-party code describes any lines of a program that can be replicated throughout different applications. This aids in the app development process itself, as the time to market, is drastically reduced via code recycling.

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The applications that make up the vast majority of today’s hyper-complex tech stacks are heavily dependent on third-party code. Unfortunately, the same vast benefits these pre-crafted components provide are often undermined by the severe security implications of third-party architecture. It’s critical for modern businesses to not only recognize these risks but actively help to stem the flow of attacks. Cutting-edge tools, including a next-gen WAF solution, may be the only path for third parties’ continued existence.

1. Third Party Code: Because Why Reinvent The Wheel?

Third-party code describes any lines of a program that can be replicated throughout different applications. This aids in the app development process itself, as time to market, is drastically reduced via code recycling. But even after the foundation of an app is laid, third-party code can be leveraged by its developers for ad tracking, customer reviews, payments, chatbots, tag management, social media integration, or other helper libraries that simplify common functions.

The sheer usefulness and availability of third-party code have seen it seep into every corner of the internet: nowadays, third-party code accounts for up to 70% of every website. In the same survey, 99% of respondents stated that the sites used and produced by their organization contain at least one third-party piece of code.

Open source describes one type of third-party code, though third-party also refers to externally developed code, the license to use which may have been purchased. Regardless of the commercial price of this code, companies have for too long ignored the social and security cost.

2. The Lurking Danger of Shadow Code

Third-party code lends itself to uber-accessible site and app development. Though these no- or low-code environments help lower the barrier of entry for eager entrepreneurs and hobbyists, it’s vital to understand the risks. Profiteering cybercriminals are more than willing to take advantage of naive or negligent developers. Sometimes, it’s not a lack of skill that lets them in, but the high-pressure push toward rapid rollout.

Attackers grouped under the Magecart umbrella have been taking advantage of third-party code since 2015. This crime syndicate relies on digital credit card theft, swiped by covertly injecting JavaScript code on e-commerce checkout pages. Magecart has wreaked an impressively high-stakes trail of destruction: Ticketmaster, British Airways and countless other online brands have all fallen foul of their attacks.

Two high-profile attacks occurred in 2020, as children’s clothes maker Hanna Andersson and British retailer Sweaty Betty were targeted. Both of these attackers are thought to have revolved around apparently-innocuous site addons. Hidden within these lines of code, however, Magecart attackers add a few key lines of JavaScript.

This third-party code often copies legitimate payment forms on an eCommerce site. However, there are crucial – tiny – modifications made. For instance, the payment information is covertly sent to an attacker-controlled server. The transaction itself is still allowed to go through, meaning that end-users are left totally in the dark. The attack on Hanna Andersson went totally unnoticed for weeks – even this represents a relatively fast discovery, with other victims remaining clueless for up to a year.

Most victims are only alerted when stolen credit card info pops up on dark web marketplaces. The cost is significant: Hanna Andersson was ordered to pay $400K in damages to over 200,000 customers; the exact cost to individual victims is more difficult to ascertain, but the theft of their name, shipping address, billing address, and payment card info allows attackers to conduct incredible damage. Magecart attacks actually rose in popularity throughout the Covid-19 pandemic, seeing a 20% increase, while the average detection time hit 22 days.

Magecart may represent malicious third-party code; but even tested, open-source code can accidentally cause one of the greatest security problems of this decade. Log4j describes an open-source logging library that has become one of the most important pieces of architecture throughout the web, responsible for relaying vital logging info back to the developer and maintenance team. In 2021, however, it was discovered that the log4j library was critically vulnerable to remote code execution. This placed hundreds of millions of devices at severe risk, as the flaw was also relatively simple to exploit.

Forgoing third-party code altogether isn’t realistic. Over 60% of websites across the world run on Apache and Nginx servers, while 90% of IT leaders rely on enterprise open-source code regularly. All modern software is built from pre-existing components, and rebuilding these functions from scratch would require massive investments in time and money to produce even relatively simple applications.

3. You Can’t Patch Your Way Out of This One

Once bundled into an application, third-party code can be difficult to test, and even harder to secure. Patches are wholly dependent on the developers; even for active, well-meaning devs, such as those maintaining the log4j functionality, patching takes critical time.

Fear not: a comprehensive security solution can offer a number of tools to virtually patch – and ultimately stop attackers in their tracks. One such tool is the Web Application Firewall (WAF). This sits in between the application and the end-user, monitoring and filtering passing traffic. Next-gen WAFs offer automatic policy creation, along with rapid rule propagation, explicitly to broaden the safety net that third-party code requires.

While the traditional WAF has focused primarily on monitoring external connections, Web Application and API Protection (WAAP) describes a more comprehensive suite of protection. This incorporates the firewall-based approach of the WAF, with a greater focus on APIs. These pieces of code provide programmatic access across different apps and have historically been a major weak point in organizational defenses.

Finally, Runtime Application Self-Protection (RASP) offers a compelling next step toward automated protection. Instead of sitting externally to the app’s own code, RASP acts as a plugin, attaching to an application’s internals. Thanks to its internal view of an app, RASP can monitor its behaviors and map the typical connections and privileges that occur under the hood. Once a baseline behavior is established, RASP can then automatically detect – and critically, shut down – suspicious behavior.

With a proactive suite of virtual patching measures in place, your security is empowered to keep pace with DevOps, whilst helping nullify the threat of cybercriminals and the ensuing lawsuits.

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