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How to choose the database and the comparison between DynamoDB and Hadoop and MongoDB, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible way.

How users choose the database that best meets the current business needs usually depends on the technology of their development team and the applications they have used. It is important to know which database system best suits the current and future needs of the user company. Databases play a vital role in all industries and organizations. Therefore, whether the most appropriate database system can be selected from the two dimensions of demand and price may become a watershed between project and strategic success or failure.

All of these systems are not necessarily interchangeable with each other, and in some cases, they are more like comparing apples and oranges. However, because they usually fall into the category of NoSQL (NoSQL generally refers to non-relational databases, NoSQL databases promote scalability and help Web applications reduce development time), these systems are usually compared together.

Therefore, let's start with an introduction to each system and then compare it.

What is DynamoDB?

DynamoDB is a well-crafted NoSQL database service by Amazon that can be used as part of the Amazon Web Services (AWS) portfolio.

DynamoDB originated from the Dynamo system, a highly available key value (key-value) storage system. Amazon set up the system to avoid system disruptions like those seen in holiday e-commerce promotions in 2004.

Initially, because of the complexity of Dynamo operations and the tradeoff between data consistency, performance, query flexibility, and reliability, only a small number of teams within Amazon adopted the Dynamo system.

And during this period, Amazon developers prefer to use the SimpleDB NoSQL database, which can ease the management of the user database. However, due to some limitations of SimpleDB, its usage scenarios are ultimately limited.

DynamoDB, launched in 2012, is AWS's database service designed to break the limitations of Dynamo and SimpleDB.

What is Hadoop?

The Apache Hadoop software library is a framework that allows distributed processing of large data sets between computer clusters using a simple programming model. It is designed to scale from a single server to thousands of machines, each providing local computing and storage.

The purpose of Hadoop itself is to detect and handle faults in the application layer without relying on hardware to provide high availability. At a deeper level, Hadoop is actually modular. This means that users can replace any part of it and build it into a variety of software tools. This process achieves a very flexible, effective, and robust architecture.

What is MongoDB?

MongoDB is a non-tabular and open database created by MongoDB Inc. The sponsors initially focused on creating a platform that fully uses open source, but in order to obtain an existing database customer base to meet their needs of building services in the cloud, they began to create personal database systems.

Aware of the possibility of creating database software, the team shifted its focus to creating MongoDB. MongoDB, released in 2009, aims to create a technical foundation that enables development teams to achieve distributed system design, document data models, and a unified experience.

In 2016, MongoDB launched MongoDB Atlas, a cloud-hosted database service. MongoDB Atlas provides authentic MongoDB services that allow users to get rid of specific operational tasks.

Now let's talk about the difference.

Ease of use, setup, and management

DynamoDB

DynamoDB's managed service frees users from the underlying infrastructure and interacts with the database only through remote endpoints. Users do not have to worry about operation problems or other hardware regulations when using DynamoDB, which makes DynamoDB very easy to use.

Hadoop

Hadoop has a variety of settings and no need for abstraction. (abstraction: data abstraction is a mechanism that only exposes interfaces to users and hides specific implementation details.) Managing Hadoop can be achieved only on the command line (command-line). Of course, this means that the user needs to be familiar with the command line and how to set up the hardware. Because of its complexity, several companies, such as Cloudera, have developed products around Hadoop to help users reduce the complexity of managing Hadoop.

If done well, using the products of these third-party companies can save users thousands of personnel costs (because hiring Hadoop engineers usually costs more than $150000).

MongoDB

MongoDB is not a SaaS service, it is one of the easiest data systems to manage directly. Users can easily download and quickly start interacting with MongoDB.

Quality support

DynamoDB

DynamoDB users can get quality support through community support forums, enterprise support, ServerFault, and Stack Overflow.

The DynamoDB community provides sample applications, drivers, extenders, and support tools. In addition, because DynamoDB is part of AWS, users can get further support from Amazon directly according to the scale of their business.

Hadoop

A number of companies provide commercial services for Hadoop and provide professional technical support. Hadoop has been around for a long time and has a number of community support forums, support tools and course support to help users improve their ability to use the system for management and development.

Personally, if users are using Hadoop raw software, we think Hadoop may be one of the systems where it is difficult to obtain quality support. However, with so many third parties involved, we think most large companies can think of Hadoop as a data storage system.

MongoDB

MongoDB provides community support forums, ServerFault and Stack Overflow. Its users can also get enterprise support 24 hours a day, seven days a week. In addition, the MongoDB community organizes information about events, MongoDB University, user groups and webinars.

Database structure

DynamoDB

DynamoDB has properties, items, and tables as its core parts for users to use frequently.

The table involves many items, and a single item is a combination of attributes.

In addition, DynamoDB uses a master code (primary key) to specifically identify individual items in the table.

Higher query flexibility can be achieved by using secondary indexes.

MongoDB

MongoDB uses doc files similar to JSON format when storing schema free data.

The collection of documents in MongoDB does not contain predefined columns and structures, which may vary from document to document. Some of the features of MongoDB in a relational database include:

Query language is easy to read.

Strong consistency.

Because of its free schema, MongoDB allows you to create a document without first creating the document structure.

The main comparisons between MongoDB and relational database management systems (RDBMS) include:

Table | column | value | record

Compared with MongoDB, it includes:

Collection | key | value | document

This approach means that the collection of MongoDB is similar to the table of RDBMS. In addition, documents are similar to records.

Hadoop

Hadoop does not qualify data structures. In essence, it accepts only the data types used on the system. Hadoop adopts read-time mode, which improves its versatility to all data sets.

All data in Hadoop is stored as a file system, and data warehousing architectures such as Hive and Immpala, which are based on the Hadoop file system, enable users to view the underlying data in a table format.

If the user wants to manage Hadoop through the Hadoop raw software, this will become very complicated. Because the file types selected and encoded by the user play a huge role in everything from speed to space, the undo operation can also become very difficult.

Users' commercial rights

DynamoDB

DynamoDB is still a popular choice in gaming and the Internet of things (IoT). If the user uses the AWS stack and needs a NoSQL database, then using DynamoDB is a good choice. Note: once using DynamoDB, users may not be able to access embedded data structures as they do on MongoDB.

Hadoop

Hadoop is a popular choice in large enterprises, because large enterprises need server clusters, and specialized data management, programming skills and high-cost implementation are not a problem for these server clusters.

Hadoop can also play an active role in building the enterprise data center of the future. It may be difficult to manage (depending on how the user decides to manage, with or without a third party), but it also brings many advantages.

MongoDB

MongoDB is an excellent choice for caching and scalability (scalability) features.

MongoDB also plays an important role in Web development, making it easy to transfer document-style data from back-end to front-end. For companies that create content management systems, choosing MongoDB makes it easy to manage data.

Performance problem

DynamoDB

DynamoDB has the following outstanding performance problems:

DynamoDB's pricing model is very expensive.

Low latency reads are not low enough.

Parallel writes across regions result in data loss, and reads across regions cannot be highly consistent.

It is difficult to set up a continuous integration / continuous delivery (CI/CD) pipeline.

Troubleshooting is difficult (simple operations such as identifying the exact key that caused the partition to become hot are also complex).

Persistence and consistency application scenarios are not yet widespread.

Incompatible ACID transactions and consistent secondary indexes.

Hadoop

Hadoop has the following outstanding performance problems:

DataNode and NameNode (there are two types of nodes in HDFS, NameNode and DataNode, respectively) slow down.

Localization of MapReduce data.

The performance of TaskTracker and its impact on time intervals.

MongoDB

MongoDB has the following outstanding performance problems:

It is important to design an index that combines access patterns and schemas.

The problem of dealing with large objects and large array exceptions.

Security and durability settings are still worrying.

There is no optimized query module (Query optimizer, the optimizer module that optimizes SELECT statements).

In addition to these differences, users can always see supporting tools floating on the system to further support data system management.

Let's take a look at some tools:

Rockset

Rockset is a scalable and reliable search and analysis service in the cloud. Using only SQL query language, you can build fast operational applications on a TB-level data scale.

This is the greatest benefit of Rockset. With the Rockset tool, the user's team does not need to be familiar with another query language.

NoSQLBooster

NoSQLBooster is the graphical user interface (GUI) used to connect to the management MongoDB. In addition, it allows users to query using both MongoDB syntax and SQL syntax.

Therefore, it not only makes it easier to manage the database (think about the scenario when using SQL Server Management Studio), but also makes it easier for analysts to run queries to answer business questions.

Sqoop

Apache Sqoop (TM) is a tool for efficient transfer of bulk data between Hadoop and structured data stores such as relational databases. This type of tool helps simplify interaction with Hadoop and can be called an ETL tool.

Conclusion

The three database systems, DynamoDB,Hadoop and MongoDB, are so different that they are not always used interchangeably. And each database has its advantages and disadvantages and use cases.

The highlighted content is designed to help users better choose their own database system. According to the size of their organization, users can handle a variety of data types, access to effective application management services, and more by using any of these database systems.

This is the answer to the question about how the company chooses the database and the comparison between DynamoDB and Hadoop as well as MongoDB. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel for more related knowledge.

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