Home Big Data MongoDB vs DynamoDB Head-to-Head: Which Ought to You Select?

MongoDB vs DynamoDB Head-to-Head: Which Ought to You Select?

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MongoDB vs DynamoDB Head-to-Head: Which Ought to You Select?

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Databases are a key architectural part of many functions and providers.

Historically, organizations have chosen relational databases like SQL Server, Oracle, MySQL and Postgres. Relational databases use tables and structured languages to retailer knowledge. They normally have a hard and fast schema, strict knowledge varieties and formally-defined relationships between tables utilizing overseas keys. They’re dependable, quick and help checks and constraints that assist implement knowledge integrity.

They aren’t excellent, although. As firms grow to be more and more digital, they typically start producing large quantities of knowledge, they usually want a spot to retailer it. Relational databases scale up nicely, however might be painful to scale out when an organization has extra knowledge than a single database server can handle.

Alternatively, non-relational databases (generally known as NoSQL databases) are versatile databases for large knowledge and real-time internet functions. These databases have been born out of necessity for storing giant quantities of unstructured knowledge. NoSQL databases do not at all times provide the identical knowledge integrity ensures as a relational database, however they are much simpler to scale out throughout a number of servers.

NoSQL databases have grow to be so common that large firms depend on them to retailer tons of of terabytes of knowledge and run hundreds of thousands of queries per second. So why have NoSQL databases grow to be so common in comparison with conventional, relational databases?

For one, NoSQL databases can settle for any sort of knowledge: structured, unstructured or semi-structured. This flexibility makes them the go-to database for a lot of use circumstances. Secondly, NoSQL is schemaless, so database objects can have fully totally different buildings from each other. And as talked about, as a result of their architectures, NoSQL databases are simpler to scale horizontally than relational databases.

There are numerous NoSQL databases accessible available in the market. Two common choices are MongoDB and Amazon DynamoDB, and designers typically discover themselves selecting between the 2. On this article, we’ll examine MongoDB and Amazon DynamoDB to one another and spotlight their vital variations. We’ll embrace their execs and cons, variations in knowledge varieties, and focus on components like price, reliability, efficiency and safety.

Earlier than evaluating MongoDB to DynamoDB, let’s take an in-depth take a look at every resolution to know what they’re, their traits and their benefits and downsides.

In This Nook, MongoDB

MongoDB is a NoSQL, document-oriented normal function database administration system. It’s optimized for low latency, excessive throughput and excessive availability. It additionally helps a JavaScript-based question language to run instructions and retrieve knowledge, with official consumer drivers accessible for over a dozen programming languages. It’s a cross-platform, open-source non-relational database that shops knowledge as collections of paperwork.


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MongoDB makes use of BSON internally to retailer paperwork, which is a binary illustration of JSON that totally helps all the options of JSON with help for extra knowledge varieties, extra environment friendly compression and simpler parsability. Whereas MongoDB collections can have a schema towards which the database validates new paperwork, schema validation is non-obligatory.

MongoDB’s Traits

MongoDB is a general-purpose database. It will possibly serve varied masses and a number of functions inside an utility. It additionally has a versatile schema design, which means there’s no set schema to outline easy methods to retailer knowledge, and it scales each vertically and horizontally. MongoDB takes under consideration safety features equivalent to authentication and authorization. It additionally has a doc mannequin that maps to things in utility code, making it simple to work with knowledge.

MongoDB’s Professionals

  • Flexibility: MongoDB has versatile database schemas. You possibly can insert data into the database with out worrying about matching standards or knowledge varieties. MongoDB helps extra native knowledge varieties than DynamoDB, and it helps you to nest paperwork.
  • Programs Design: Past accommodating giant volumes of quickly altering structured, semi-structured and unstructured knowledge, MongoDB permits builders so as to add to the schema as their wants change.
  • Information Mannequin: In comparison with DynamoDB, MongoDB helps common JSON and superior BSON knowledge fashions equivalent to int, lengthy, date, timestamp, geospatial, floating-point and Decimal128.
  • Runs Wherever: This resolution can run wherever, so customers future-proof their work with out fearing vendor lock-in.
  • Price: MongoDB has a free, open-source model if you’re price aware. They’ve additionally just lately launched a pay-as-you-go, serverless pricing possibility for MongoDB Atlas, their managed cloud providing.

MongoDB’s Cons

  • Reminiscence Use: MongoDB must hold its working set in RAM to realize acceptable efficiency. This reliance on RAM makes MongoDB too costly for a lot of use circumstances.
  • Information Duplication: Duplication occurs as a result of, in MongoDB, customers have a tendency to make use of nested paperwork as a substitute of normalized tables like in a relational database. In some circumstances this can be as a result of denormalization that should happen as a result of MongoDB doesn’t help excessive efficiency JOINs, and as a substitute makes use of a knowledge that belongs collectively is saved collectively philosophy to keep away from using JOINS completely. This limitation could cause knowledge sizes, and the associated prices, to climb.
  • Indexing: MongoDB helps easy indexes and complicated compound indexes containing a number of doc properties. As with most databases, poorly designed or lacking indexes can sluggish reads and writes, because the index should replace each time somebody inserts a brand new doc in a group.

And, in This Nook, DynamoDB

Amazon DynamoDB is a quick, versatile, NoSQL database. It’s appropriate for all functions that want constant latency at any scale. It’s a totally managed NoSQL database that’s perfect for doc and key-value fashions. Amazon developed DynamoDB as a managed database for functions requiring comparable, easy question patterns.


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DynamoDB can scale on-demand to help nearly limitless learn and write operations with response time beneath single-digit milliseconds. It’s excellent for cellular, internet, gaming and promoting know-how.

DynamoDB’s Traits

DynamoDB is serverless and scales horizontally to help tables of any measurement, making it good for large-scale efficiency. Plus, question efficiency doesn’t degrade with database measurement when querying by key. It additionally has a versatile schema that lets you rapidly adapt tables as your wants change with out restructuring the desk schema (as required in relational databases).

DynamoDB additionally gives world tables, albeit at an additional price. These tables replicate your knowledge throughout AWS Areas, making it simple on your app to domestically entry knowledge within the chosen areas. DynamoDB additionally constantly backs up your knowledge to forestall knowledge loss. It encrypts your knowledge for improved safety, and is ideally fitted to enterprise functions which have strict safety necessities.

DynamoDB’s Professionals

  • Customizable: The DynamoDB database might be modified in accordance with your app’s priorities.
  • Quick: DynamoDB delivers wonderful efficiency, regardless of what number of data you retailer or how typically you question it by key.
  • Scalability: DynamoDB scales seamlessly, whatever the site visitors ranges.
  • Pricing: DynamoDB makes use of a pay-as-you-go, throughput-based pricing method the place totally different inputs might have an effect on costs. This will help to optimize your prices as they may fluctuate together with your workload, however may trigger your pricing to be unpredictable.

DynamoDB’s Cons

  • Restricted Question Language: DynamoDB has a restricted question language in comparison with MongoDB. It’s because DynamoDB is a key-value retailer and never a full doc database. Each DynamoDB file has two keys: a partition key and a form key. Each question should present one partition key, and may optionally specify a single worth or a spread for the kind key. That’s it.
  • Restricted Indexing: In comparison with MongoDB, the place indexing your knowledge comes at no further price, DynamoDB indexes are restricted and complicated. Amazon sizes and payments the indexes individually from knowledge.
  • Pricing: DynamoDB makes use of a pay-as-you-go, throughput-based pricing method the place totally different inputs might have an effect on costs. This will help to optimize your prices as they may fluctuate together with your workload, however may trigger your pricing to be unpredictable.

Head-to-Head Desk of MongoDB vs DynamoDB

Each Amazon DynamoDB and MongoDB are extensively used, extremely scalable and cloud-compatible NoSQL databases. Regardless of these similarities, they’ve some key variations. The desk beneath explores these additional:

MongoDB DynamoDB
Supply MongoDB is open-source and might be deployed wherever in most clouds and/or on premises. DynamoDB is from the AWS ecosystem and may solely be used inside AWS.
Administration MongoDB can both be self-managed or totally managed with the MongoDB Atlas database as a service. DynamoDB is a totally managed resolution. Amazon handles all server updates, patch updates, and {hardware} provisioning.
Safety Builders have to spend further time upfront reconfiguring safety on MongoDB, particularly when self-managed. It’s because it runs with defaults allowing unrestricted and direct entry to knowledge with out authentication. MongoDB Atlas requires setup of authentication and community entry by way of IP entry controls or VPC peering. Safety for DynamoDB begins out restrictive and incorporates with AWS IAM Coverage infrastructure.
Database construction MongoDB’s database construction is product of JSON-like paperwork comprising collections, keys, values, and paperwork. Paperwork can comprise nested paperwork. DynamoDB’s database construction helps both blobs or paperwork as values.
Index use MongoDB helps as much as 64 mutable indexes per assortment, permitting the doc’s construction to alter dynamically. DynamoDB helps as much as 20 mutable world indexes per desk, which aren’t appropriate with underlying knowledge, and as much as 5 native indexes which can’t be modified after desk creation.
Programming language MongoDB is written in C++ and helps programming languages like C, C++, Go, Java, JavaScript, PHP, Perl, Ruby, Python and extra. DynamoDB helps programming languages like Java, JavaScript, Node.js, .NET, PHP and extra.
Information sort and measurement restriction MongoDB helps varied knowledge varieties, and permits doc sizes of as much as 16MB. DynamoDB has restricted help for knowledge varieties, and permits merchandise sizes of as much as 400 KB.
Trade use Corporations use MongoDB for cellular apps and content material administration methods (CMSs). MongoDB can also be wonderful for scalability and caching. The gaming and Web of issues (IoT) industries extensively use DynamoDB.
Price MongoDB makes use of a hard and fast pricing mannequin the place you pay for provisioned assets forward of time. Pricing relies on RAM, I/O and storage for MongoDB Atlas, plus server and sysadmin time if you’re internet hosting MongoDB your self. Prices are constant, however will not be optimum for variable workloads. DynamoDB makes use of a variable pricing mannequin the place you pay for what you employ, which relies on a throughput mannequin with extra fees for options like backup and restore, on-demand capability, streams, change knowledge seize (CDC) and others. This will trigger your prices to be much less predictable.
Querying MongoDB has a wealthy question language. You possibly can apply it in varied methods: single keys, ranges, graph transversals, joins and extra. DynamoDB’s querying is just accessible in native secondary indexes (LSI) and world secondary indexes (GSI).

Which Database Ought to I Select, MongoDB or DynamoDB?

DynamoDB and MongoDB are extremely profitable fashionable options for conventional database methods, equivalent to MySQL, PostgreSQL and others. When choosing your database, that you must think about components equivalent to scale, person necessities, deployment methodology, storage necessities and performance.

When you’re searching for an AWS-native resolution with MongoDB-like capabilities, you may also think about Amazon DocumentDB. Whereas DocumentDB is just not based mostly on the MongoDB server, iIts skills are near MongoDB, and is appropriate with the MongoDB 3.6 and 4.0 APIs. You possibly can even use DocumentDB as a drop-in alternative for MongoDB as it’s MongoDB appropriate.

MongoDB and DynamoDB are each strong NoSQL databases that meet and clear up varied person wants. You must rigorously think about whether or not or not a database totally fits your use case. Every database has distinctive benefits, so consider your long-term cloud technique and an utility’s particular wants when deciding which NoSQL database to pick out.

No matter which NoSQL database you employ, pairing it with a real-time analytics database is a standard sample, as neither MongoDB or DynamoDB is primarily an analytical database. When you’re constructing user-facing knowledge functions utilizing your knowledge saved in MongoDB or DynamoDB, think about Rockset, which permits real-time SQL analytics in your MongoDB or DynamoDB NoSQL database.


Rockset is the main real-time analytics platform constructed for the cloud, delivering quick analytics on real-time knowledge with shocking effectivity. Be taught extra at rockset.com.



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