5 Use Circumstances for DynamoDB

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Internet-based purposes face scaling because of the development of customers together with the growing complexity of information visitors.

Together with the fashionable complexity of enterprise comes the necessity to course of information sooner and extra robustly. Due to this, commonplace transactional databases aren’t at all times the most effective match.

As a substitute, databases comparable to DynamoDB have been designed to handle the brand new inflow of information. DynamoDB is an Amazon Internet Providers database system that helps information constructions and key-valued cloud companies. It permits customers the good thing about auto-scaling, in-memory caching, backup and restore choices for all their internet-scale purposes utilizing DynamoDB.

However why would you need to use DynamoDB and what are some examples of use circumstances?

On this submit, we’ll cowl simply that. We are going to structure the advantages of utilizing DynamoDB, and description some use circumstances in addition to a number of the challenges.

Advantages of DynamoDB for Operations

First, let’s focus on why DynamoDB may be helpful.


Efficiency and scalability

Those that have labored within the IT trade know that scaling databases can each be troublesome and dangerous. DynamoDB offers you the power to auto-scale by monitoring how shut your utilization is to the higher bounds. This may permit your system to regulate in response to the quantity of information visitors, serving to you to keep away from points with efficiency whereas lowering prices.

Entry to regulate guidelines

As information will get extra particular and private, it turns into extra necessary to have efficient entry management. You need to simply apply entry management to the correct individuals with out creating bottlenecks in different individuals’s workflow. The fine-grained entry management of DynamoDB permits the desk proprietor to realize a better stage of management over the info within the desk.

Persistence of occasion stream information

DynamoDB streams permit builders to obtain and replace item-level information earlier than and after adjustments in that information. It is because DynamoDB streams present a time-ordered sequence of adjustments made to the info throughout the final 24 hours. With streams, you possibly can simply use the API to make adjustments to a full-text search information retailer comparable to Elasticsearch, push incremental backups to Amazon S3, or keep an up-to-date read-cache.

Time To Dwell

TTL or Time-to-Dwell is a course of that lets you set timestamps for deleting expired information out of your tables. As quickly because the timestamp expires, the info that’s marked to run out is then deleted from the desk. By this performance, builders can preserve monitor of expired information and delete it robotically. This course of additionally helps in lowering storage and chopping the prices of guide information deletion work.

Storage of inconsistent schema objects

In case your information objects are required to be saved in inconsistent schemas, DynamoDB can handle that. Since DynamoDB is a NoSQL information mannequin, it handles much less structured information extra effectively than a relational information mannequin, which is why it’s simpler to handle question volumes and affords excessive efficiency queries for merchandise storage in inconsistent schemas.

Automated information administration

DynamoDB always creates a backup of your information for security functions which permits homeowners to have information saved on the cloud.

Seesaw Case Study

5 Use Circumstances for DynamoDB

One of many causes individuals don’t use DynamoDB is as a result of they’re unsure whether or not it’s a good match for his or her venture. We wished to share some examples the place corporations are utilizing DynamoDB to assist handle the bigger inflow and of information at excessive speeds.


Duolingo, an internet studying web site, makes use of DynamoDB to retailer roughly 31 billion information objects on their net server.

This startup has round 18 million month-to-month customers who carry out round six billion workouts utilizing the Duolingo app.

As a result of their software has 24,000 learn models per second and three,300 write models per second DynamoDB ended up being the correct match for them. The workforce had little or no data about DevOps and managing giant scale techniques after they began. Due to Duolingo’s world utilization and want for customized information, DynamoDB is the one database that has been capable of meet their wants, each by way of information storage and DevOps.

Additionally, the truth that DynamoDB scales robotically meant that this small startup didn’t want to make use of their builders to manually alter the scale. DynamoDB has simplified in addition to scaled to fulfill their wants.

Main League Baseball (MLB)

There’s rather a lot we take without any consideration after we watch a recreation of baseball.

For instance, do you know there’s a Doppler radar system that sits behind house plate, sampling the ball place 2,000 instances a second? Or that there are two stereoscopic imaging gadgets, normally positioned above the third-base line, that pattern the positions of gamers on the sphere 30 instances a second?

All these information transactions require a system that’s quick on each reads and writes. The MLB makes use of a mix of AWS elements to assist course of all this information. DynamoDB performs a key function in guaranteeing queries are quick and dependable.

Hess Company

Hess Company, a widely known power firm, has been engaged on the exploration and manufacturing of pure fuel and crude oil.

This enterprise requires strategizing completely different monetary planning which impacts administration on the entire. To streamline their enterprise processes, Hess turned in the direction of DynamoDB by shifting its E&P (Power Exploration and Manufacturing) venture onto AWS.

Now DynamoDB has helped the corporate in separating potential consumers’ information from enterprise techniques. Furthermore, the operational infrastructure of DynamoDB helps them to deal with information successfully and get optimized and well-managed outcomes.

GE Healthcare

GE is well-known for medical imaging gear that helps in diagnostics by means of radiopharmaceuticals and imaging brokers.

The corporate has used DynamoDB to extend buyer worth, enabled by cloud entry, storage, and computation.

The GE Well being Cloud gives a single portal for healthcare professionals everywhere in the US to course of and share pictures of affected person circumstances. This can be a nice benefit for diagnostics. Clinicians can enhance remedies by means of entry to this healthcare information.


NTT Docomo, a preferred cell phone working firm, has constructed a fame for its voice recognition companies, which want the most effective efficiency and capability.

To cater to those necessities, Docomo turned in the direction of DynamoDB which has helped the corporate scale in the direction of higher efficiency.

With their rising buyer base, Docomo has introduced a voice recognition structure into use, which helps them carry out higher even throughout visitors spikes.

Together with all these circumstances, promoting expertise corporations additionally rely closely on Amazon DynamoDB to retailer their advertising information of various sorts.

This information consists of person occasions, person profiles, visited hyperlinks and clicks. Generally, this information additionally consists of advert concentrating on, attribution, and real-time bidding.

Thus, advert tech corporations require low latency, excessive request fee and excessive efficiency with out having to speculate closely in database operations.

That is why corporations flip in the direction of DynamoDB. It not solely affords excessive efficiency but additionally, with its information replication possibility, permits corporations to deploy their real-time purposes in a couple of geographical location.

Nonetheless, regardless of all the advantages DynamoDB isn’t at all times the best database to make use of relating to analytics.

Challenges of Analyzing DynamoDB Operational Information

DynamoDB’s focus is on offering quick information transactions for purposes. What makes DynamoDB quick on a transaction stage can really hinder it from the angle of analyzing information. Listed here are a couple of of the foremost roadblocks you’ll run into when you begin analyzing information in DynamoDB.

On-line Analytical Processing (OLAP)

On-line analytical processing and information warehousing techniques normally require large quantities of aggregating, in addition to the becoming a member of of dimensional tables, that are offered in a normalized or relational view of information.

This isn’t doable within the case of DynamoDB because it’s a non-relational database that works higher with NoSQL formatted information tables. Moreover, the final information constructions for analytics aren’t at all times effectively supported in key-value databases. In flip, it may be tougher to get to information and run giant computations.

Querying and SQL

Together with OLAP processes being troublesome to run on DynamoDB, because of the focus of DynamoDB being operational, DynamoDB doesn’t interface with SQL.

This can be a key difficulty as a result of most analytical expertise is accustomed to SQL and never DynamoDB queries. In flip, this makes it troublesome to work together with the info and ask important analytical questions.

The implications of this may be the requirement to rent builders solely to extract the info, which is dear, or being unable to investigate the info in any respect.

Indexing is dear

One other qualm relating to analytics is processing giant information units rapidly. Typically this may be alleviated with indexes.

On this case, the issue is that DynamoDB’s world secondary indexes require extra learn and write capability provisioned, resulting in extra price. Because of this both your queries will run slower or you’ll incur larger prices.

These challenges can generally be a hindrance to some corporations deciding whether or not or not they need to tackle the chance of growing on DynamoDB.

dynamodb flow chart

That is the place analytics engines like Rockset are available in. They not solely present a SQL layer that makes it simple to entry the operational information but additionally present the power to ingest the info into their information layer — which helps joins with information from different AWS information sources, like Redshift and S3.

We’ve discovered instruments like this to be useful as a result of they’ll cut back the necessity for builders and information engineers who can interface with DynamoDB. As a substitute, you are able to do your analytical work and reply the necessary questions with out being held again.

For individuals who have ever labored on an analytical workforce, it may be very troublesome to clarify to higher administration why information exists, however you’re nonetheless unable to offer insights. Utilizing layers like Rockset can take the complexity away.


As a non-relational database, DynamoDB is a dependable system that helps small, medium and enormous enterprises scale their purposes.

It comes with choices to backup, restore and safe information, and is nice for each cellular and net apps. Except for particular companies like monetary transactions and healthcare, you possibly can redesign virtually any software with DynamoDB.

This non-relational database is extraordinarily handy to construct event-driven structure and user-friendly purposes. Any shortcomings with analytic workloads are simply rectified with the usage of an analytic-focused SQL layer, making DynamoDB an ideal asset for customers.

Ben has spent his profession centered on all types of information. He has centered on growing algorithms to detect fraud, cut back affected person readmission and redesign insurance coverage supplier coverage to assist cut back the general price of healthcare. He has additionally helped develop analytics for advertising and IT operations with a purpose to optimize restricted sources comparable to staff and funds. Ben privately consults on information science and engineering issues. He has expertise each working hands-on with technical issues in addition to serving to management groups develop methods to maximise their information.


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