fabiochiu/medium-articles huggingface dataset:
Electric Vehicle Market Worth $1,212.1 Billion By 2027
By: Gaurav Shah
Tags: Japan, Electric Vehicles, New Zealand, France, China

The global electric vehicle market demand is expected to reach $1,212.1 billion by 2027, expanding at a CAGR of 38.1% over the forecast period, according to a study conducted by Grand View Research, Inc. The market is driven by initiatives taken by governments of various countries to promote manufacturing of Electric Vehicles (EVs). For instance, the Electric Vehicles Initiative (EVI), a multi-government forum, aims at increasing the adoption of EVs globally. As of now, there are thirteen countries participating in this forum, namely Canada, Chile, U.K., Germany, Sweden, Netherlands, Norway, Finland, France, China, Japan, India, and New Zealand. Several campaigns and programs have been launched under this forum such as the EV30@30 in 2017, which sets a target for 11 countries to have at least 30.0% sales of new EVs by 2030.

Rising investments in the EVs by numerous manufacturers is one of the key market drivers over the forecast period. For instance, in January 2020, General Motors announced its plan to invest USD 2.2 Billion in its Detroit plant to manufacture electric trucks and SUVs. The company plans to introduce over 20 EVs by 2023. Furthermore, in 2018, the demand for global electric cars surpassed 5 million units, more than 2 million units from 2017. China is considered as one of the major markets of electric cars along with Europe and U.S. However, lack of infrastructure is anticipated to hinder electric vehicle market growth over the forecast period.

Growing awareness regarding reduction of air pollution is propelling the demand for EVs during the forecast timeframe. EVs produce less carbon emissions as compared to conventional gasoline cars. It is estimated that EVs emit an average of 4,450 pounds of CO2 equivalents every year, which is almost half of the carbon emissions generated by conventional gasoline cars annually. Thus, EVs help in reducing air pollution and improve the air quality, thereby improving public health. This has led various government agencies promote the usage of electric vehicles. For instance, the U.S. Department of Transportation, Great Plains Institute, and Pollution Control Agency are working in tandem to accelerate the adoption of EVs in Minnesota, U.S.

Click the link below:

https://www.grandviewresearch.com/industry-analysis/electric-vehicles-ev-market

Further key findings from the report suggest:
ID.4 Style Accents Should Add Up for U.S. Consumers
By: Grant Gerke
Tags: Electric Charging, Electric Vehicles, Volkswagen, Cars

The ID.4 crossover SUV is impressive and provides a compact and cozy style that VW is known for, and the vehicle is making its way across Europe and U.S. in late 2020. A Bjørn Nyland video production.

Bjørn Nyland gives a look at the ID.4 (with an assist) from a VW executive and shows off the curious and intriguing crossover.

Updated (11/22) | VW planned to sell a number of ID.4s in California in 2020, but are focusing on Europe, where stringent 2020 CO2 mandates are already in place. A VW company spokesperson (via Automotive News) indicated that the company hasn’t changed its plan for a “50-state launch across its network of 650 U.S. dealerships” in the first half of 2021.

VW is the bad boy automotive company, caught deceiving regulators with its rigged software for its “clean diesel” line of sedans and compacts — the software restricted sulfur emissions during testing, exceeding the legal limit by 25x.

However, in 2020, VW is all in with its MEB electric production platform for multiple electric cars and released the ID.3 to solid fanfare earlier this year (see here), but the ID.4 is the next step in creating a more enduring style.

The design is a leap away from the pedestrian, compact styling of the ID.3 and could convert many Americans to stray from Tesla. The Chevy Bolt is a great EV but it does lack styling and my theory is Americans want more design from EVs. Plus, the ID.4’s heads-up-display (HUD) is another techie carrot for those new drivers.
Hummer EV
Tags: Electric Vehicles

The Quiet Revolution is here. Introducing GMC Hummer EV, the world’s first all-electric super truck. Reserve yours now.

Check out more at: https://www.gmc.com/HummerEV
I Disagree w/ Short Sellers on Blink
By: Andrew Kamal
Tags: Stocks, Electric Vehicles, Hedge Funds, Selling, Stock Market

Short sellers have been extra active recently. Many of the shorts I seen so far like $NNOX, $NIO and $MPLN didn’t go so well. Still time will tell. I believe the same applies to $BLNK. Right now, shortening a stock that surged so high in an overly saturated space seems like an easy idea. It is easy to convince people, hey this space is hot, this stock went up alot, it should crash. However, technicals are beyond assumption. People shortened $RIDE recently at $17, prior to the surge it is having now. It seems like many of the bigger short selling firms’ have been having more and more of a negative track record recently. They are going after small and mid cap tech companies that can pose high growth.

Even $ADOM, an OTC stock was dumped. As you recall, I called it at June. $ADOM went from $0.14 to $0.34 given what a different person have said about it. My target was $1 and all the technicals seemed in my favor. $ADOM hit 97 cents (so far) today. Between that time it got dumped multiple times over w/ sentiment being ruthlessly negative.

$BLNK which is a much bigger company working on really larger things, have grown in investor confidence. Tweets like the one below are in my opinion, very misleading.

Here are the facts, the market cap for $BLNK is almost a third of $SBE. Even with less market share, they still have technology and expansion strategy. Talking about R&D spend is irrelevant when considering stock technicals. Also $BLNK spent way more than $0. $BLNK was founded in 1998, and is established enough to make me believe it isn’t some get rich scheme for the founders. Citron also tried shortening $SOLO, but where were they on many forum boards earlier this year when $SOLO was crashing under $3. Investor confidence been increasing alot for a reason. This is a surging space, just as was the cryptocurrency market or dotcom boom was.

I respectively disagree again with Citron. If anybody else remembers, $BLINK was also shortened in August by Culper Research and many other times. Investor confidence still been increasing. It isn’t that I am against short selling, but all the stocks that activist firms seem to be targeting right now all look like the wrong focus.

Disclosure: Please keep in mind, everything I say is on an opinion based basis. This is not meant to be taken seriously or as actionable financial advice. Do your own due diligence and any trades/investments you do is at your own risk. We are not responsible, proceed with caution and we are trying to voice an opinion not meant to warrant action. This is solely meant to be viewed as a non actionable opinion not meant to be taken as seriously or as a form of actionable advice.
Yeah, There’s Tesla… But also, Lightyear
By: James Crawford
Tags: Lightyear One, Tesla, Electric Vehicles, Lightyear, Solar Energy

Yeah, There’s Tesla… But also, Lightyear

Photo by Charlotte Stowe on Unsplash

Yes, I am an avid fan of Tesla. Yes, they are doing industry-changing things in favor of the electric transportation revolution.

However, let us not forget about Lightyear.

For those who don’t know, Lightyear is a startup in the Netherlands creating the first production solar electric car. Like Tesla, they are starting with a high margin and highly-priced vehicle in hopes of scaling up production. Also, to help with pushing out future solar electric vehicle types like a crossover/SUV or perhaps a truck.

Not only have they made this vehicle super-efficient, but it barely has to be plugged in to charge. You could leave it out in the sun for a whole weekend and get a decent amount of range, depending on your geographical location. Throw in the fact that it can potentially reach a range of 725 km, under the WLTP standard of measurement, and you’ve got one epic car. True energy independence with less reliance on the grid for electrons.

So, why are they pushing a solar electric car? Because they believe any vehicles that put less strain on our energy grid and other infrastructure, the better. As great as converting everyone to electric transportation, some would argue that our current grid won’t be able to support the eventual overflow of said electric vehicles.

To counter, yes they are correct. The current infrastructure won’t be able to support all future electric cars. However, there’s an ample amount of ideas and plans in place to change this. Examples of this include on-shore/off-shore wind, solar, geothermal along with several examples of energy storage.

Potentially using the ocean as energy storage via a closed-loop system is my personal favorite. Joe Scott covered said topic in this video below:

All in all, the future is exciting and I can’t wait to drive an EV. Having the same EV with solar panels embedded in such a way that it’s actually beneficial to the owner… would be even better. So, I’m going to continually keep a constant eye on Lightyear.
How To Take India Towards An Electric Vehicle’s Future?
Tags: Electric Vehicle Baroda, El Vehicle Manufacturers, Ev Manufacturers, Top Electric Bike Brand, Electric Vehicle

Electric Bikes

In the past few years, there has been a rise in the collective consciousness of people across the globe where we, as civilization, have realized that we cannot survive without our home planet: Earth. The major reason for this kind of rise is due to the increase in pollution levels and the depletion of our natural resources which is accelerated by the former. In the most recent years, there has been a development in the people’s approach towards the increasing climate change. Along with the movements for saving the ocean, protecting forests, the major one has been to swap traditional sources of fuels for alternative energy. One of the major shifts in alternative energy has been in regard to vehicles and specifically using cars and bikes that run on electricity. And leading India in this global shift is Joy E-Bike, a part of Wardwizard Group.

Before we jump into the conversation about How we can take India towards an electric future, let us try to understand why E-Bikes have increasingly become popular.

The very simple reason is the fact that E-Bikes are extremely economic in nature. They’re straightforward to operate, and if you are purchasing an E-Bike in India from one of the best e-bikes manufacturers, also known as Joy E-Bike, you are 100% going to get value for money. As of yet, the Government of India has not put a compulsion on e-bike riders to get a registration or even a license for that matter. So you basically go to a showroom of Joy E-Bike, get your electric bike, and then, you’re good to ride it!

Since their operation in the year 2016, Joy E-Bike has contributed towards rapidly increasing the community of E-Riders in India. This is one of the major reasons why ET declared Joy E-Bike as, “The Top Electric Bike Brand of 2020”. For this rapidly growing community of E-Bikers, there have to be a few things that we need in place which will help us to make sure that we are able to accommodate E-Bikes in our day-to-day transportation.

The most important factor that we need for e-bikes is to ensure that like petrol stations on an average of 10kms, there are charging stations in the same manner. This could either be done by incorporating charging stations at petrol stations itself or by erecting new infrastructure for the same.

Another thing that we need to make sure that every Indian’s next bike is an electric one is to educate them at a very early stage. Arranging talks by industry experts, environmentalists, and others at schools, colleges, universities, and other places. We must also ensure that the stigmas created by the early-on models of e-bikes are eradicated root and stem.

To encourage more and more people to produce e-bikes on a large scale, the government of India must also grand stimulus as well as concessions to the producers who intend to produce e-bikes. Till that happens, Joy E-Bike is open to collaborating with various other electric vehicle manufacturers in India through their two other OEM Plants.
Fusion of cryptocurrency and electromobile? It is possible! In the future, you will pay for electricity by TCR.
Tags: Blockchain, Electric Vehicles, Cryptocurrency, Cryptocurrency News, Cryptocurrency Investment

According to Chris Midgeley, head of S&P Global Platts’ analytics, the production of electric cars is growing every year. By 2040, the number of electric cars in the world will exceed 400 million. For example, based on various estimates, the number of electric vehicles produced globally was about 7.2 million by the end of 2019. Along with production, the ecosystem is developing, which is necessary for the functioning of the car. First of all, an integral part of an electric car is an electric charger. Tecra also follows and seeks to contribute to global trends.

You can read the whole article on our website https://tecra.space/news/fusion-of-cryptocurrency-and-electromobile-it-is-possible-in-the-future-you-will-pay-for-electricity-by-tcr

Polish language https://tecra.space/pl/aktualnosci/polaczenie-kryptowaluty-i-pojazdu-elektrycznego-to-mozliwe-w-przyszlosci-zaplacisz-za-prad-kryptowaluta-tcr

Russian language https://tecra.space/ru/novosti/obedinenie-kriptovaliuty-i-elektromobilia-eto-vozmozhno

Chinese language https://tecra.space/cn/news-cn/zai-tecrazhong-jiang-jia-mi-huo-bi-yu-dian-dong-qi-che-rong-he-de-ke-neng-xing

Korean language https://tecra.space/kr/news-kr/crypto-electric-cars-fusion-kr

Enjoy!
Charging Your EV Like Your Smartphone
By: Steve Levine
Tags: Tesla, Electric Vehicles, Charging Electric Vehicle, Batteries Industry

Photo: Smith Collection/Gado/Getty Images

Last week, I reported that electric vehicles won’t break decisively into the mass market until consumers see ubiquitous infrastructure where they can charge up in about 15 minutes — that Americans want the “gas station experience.” Readers of The Mobilist who own EVs wrote back to object, arguing that combustion-driving motorists will see soon enough that they can charge at home. (See comments underneath the story.)

We will know the answer with certainty by mid-decade, when carmakers debut their dozens of announced EV SUVs, pickups, and sedans. But polls (here and here) suggest that consumers really do want to know that charging is out there so they definitely will not be stranded. And GM, VW, and Ford are in fact building some infrastructure; Tesla already has a robust system.

As an analogy, consider your cellphone. You can and do charge it at home. Yet everywhere — at airports, Starbucks, and other public places — merchants have installed oodles of new electric power sockets. It’s because you or certainly people you know — worried they may run out of battery — demand the ability to top up almost anywhere in public.
GM Won’t Serve As the Electric Pickup Manufacturing Arm of Startup Nikola
By: Steve Levine
Tags: Tesla, Electric Vehicles

In statements today, GM said it will sell fuel cells to Nikola for its electric semi-truck, but it omitted any mention of its abortive September agreement to engineer a pickup truck for the startup. At the same time, Nikola’s shares also plunged after Nikola said it will be canceling the electric Badger pickup.

In September, GM said it would engineer and manufacture the Badger, plus take a $2 billion, 11% stake in Nikola. The deal would have provided billions in cash to GM. But it seemed to demonstrate an insecure GM, relegated to the labor pool while Nikola basked in GM’s engineering, whose much-promoted Ultium battery system would be part of the deal.

The deal began to get shaky after a short seller’s report alleged fraud at Nikola, and the startup’s founder, Trevor Milton, resigned. Since then, GM has conducted high-profile news events heralding its own coming electric Hummer pickup.
Will Chinese EVs pull a TikTok on Tesla?
By: Gonzalo Espinoza Graham
Tags: Tesla, Electric Vehicles, Tech, Electric Car, China

By now we are all familiar with the growth story of TikTok and how it grew way faster than all western social networks, now Chinese EV stocks have been on a massive bull run and yesterday, possibly the most hyped EV company -NIO- announced their 2020 Q3 results:

Sales increased 147% YoY, margins finally went positive, all that good stuff.

But how does young NIO compare to Tesla’s early days? The deliveries per quarter tells the growth story:

Deliveries Data: Link

After 10 quarters of deliveries, NIO is sitting at a rate of 12.2k deliveries per quarter, this is in contrast to Tesla’s end of first 10 quarters of delivering cars (back in Q4 2014) where they hit a rate of 9.8k deliveries per quarter.

NIO’s deliveries have been growing at an average rate of 40% QoQ, versus Tesla’s deliveries back in the day growing at 20% QoQ. This is despite NIO’s early ramp having to deal with the pandemic and yet still managing to beat young Tesla vis-à-vis.

So who is winning? It’s hard to tell right now. As Tesla has shown us, linear growth and exponential growth look the same in the early days. NIO’s CEO William Li talks about raising production quantities in 2021 to 150k-300k per annum (37.5k-75k per quarter), this would put NIO way ahead of Tesla’s historic ramp up.

The assumption is that the Chinese market is bigger (just based on population), but also easier to build up: Wealth is spread much less evenly in China in contrast to North America or Europe. Most of Chinese EV customers are located in coastal cities, while rural China is poor in comparison. This means that current EVs with not-so-great range present a stronger value proposition, and the reach of the charging network does not have to be as extensive as that of the US.

While NIO gets to lean on the technology and product awareness Tesla developed over the years, they also have to deal with the increased pressure of directly competing with it as well as many other Chinese EVs (Li, XPeng, BYD, et al).

A wave of price cuts for Tesla’s MIC (Made in China) vehicles is on the horizon as they continue to ramp up production. The price cuts could be greater than expected, with rumours of a Lithium Iron Phosphate battery pack in the cards for Tesla. This chemistry was previously written off for its low performance, but the increased efficiencies of powertrains and the pursue for cheaper EVs may have made them viable again. This would be a strong blow to NIO’s momentum, stirring up an intense rivalry.
Relational and Non-Relational Databases
By: Abinaya Rajesh
Tags: Rdbms, Non Relational Database, NoSQL, Relational Databases

Relational Databases

Organization of data is very important to retrieve data from the databases. It helps us to use the data later. Creating a data model is an iterative process. You can alter the tables based on the data availability and redundancy in the data. Data modeling is used by the software engineers, data engineers, data scientist and whoever uses the data. The relational and non-relational databases do different kinds of data modeling.

The most common relational databases(RDs) are PostgreSQL, Oracle, Teradata, MySQL. In relational databases, data is stored as rows and columns with a unique key that identifies a record. The database or schema is a collection of tables. A table is a group of rows sharing the same labelled elements. If you have a small data volume, you can use relational databases. Additionally, if the business requirement is changed, you can easily alter the data model based on your requirement. Data integrity is very important when you do a transaction, especially in a bank. If you require ACID transactions your business, it is supported by the relational database.

Atomicity: The whole transaction is processed or nothing is processed. For example, if money is transferred by you from your account to your friend's account, if the money detects from your account but not credited in your friend's account, the transaction is not complete. This transaction should be rolled back to the old state before you initiate the transfer.

Consistency: Only the transactions abide by the constraints and rules are written to the database otherwise the database keeps the previous state. For example, all the account number hat you put in the account columns must have the same format.

Isolation: Transactions are processed independently and securely, order does not matter. If a data in a table is altered, that table is not available to the other user until you have done the changes.

Durability: Completed transactions are saved to the database even in cases of system failure. A commonly cited example includes tracking flight seat bookings. So once the flight booking records a confirmed seat booking, the seat remains booked even if a system failure occurs.

The relational database is not of use in the below scenarios:
DBaaS Evaluation: Couchbase Cloud, MongoDB Atlas, and Amazon DynamoDB
Tags: Big Data, NoSQL, Cloud Computing

NoSQL solutions provide the scalability and agility required by modern high-load apps. With the increased performance, there come additional operational expenses, as well as effort and time burdens for deployment, configuration management, support, and troubleshooting. In response, NoSQL database as a service (DBaaS) emerged as a fully managed solution deployed in the cloud. The technical study compares the performance of three NoSQL DBaaS systems — Couchbase Cloud, MongoDB Atlas, and Amazon DynamoDB — in terms of latency and throughput while processing update-heavy activities, scans, pagination, and JOINs.

For more, read the full article.
[Scylla] 세상에서 가장 빠른 NoSQL의 Architecture
By: Daily Kiwi
Tags: Scylladb, Scylla, Architecture, Scylladb Architecture, NoSQL

ScyllaDB’s Benchmarks에서 Scylla 측에서 제공한 Benchmark 결과를 확인할 수 있습니다. Scylla 뿐만 아니라 삼성 SDS에서 진행한 POC에서는 ScyllaDB가 속도, 처리량에서 카산드라 대비 8배에서 최대 37배의 고성능을 보인 것으로 나타났습니다.

Cassandra가 JVM 기반이라 JVM이 갖는 장점들을 갖지만 동시에 메모리 관리나 Garbage Collection 같은 필수 작업을 해야하기에 단점도 존재합니다.

하지만 ScyllaDB는 C++기반의 High-performance framework인 Seastar기반으로 개발되었습니다. 또한 CPU Core 별 Data Sharding과 단일 thread 기반 processing으로 Cassandra가 갖고 있던 lock 관리나 Context Processing이 원천적으로 불필요하다고 합니다.

삼성 SDS Report에서는 다음과 같이 ScyllaDB를 정리합니다.

분산처리에 효율적으로 설계된 DB답게 Scylla Server는 Cluster, Node, Shard로 구성됩니다. 확실히 Scale out이 효율적으로 될 수 있도록 설계된 것 같습니다.

Cluster

ScyllaDB에서 Data는 한 곳에 저장되지 않습니다. 여러 노드에 나눠서 저장되고 그 노드의 묶음을 Cluster라고 합니다. Data는 multi-datacenter replication을 이용하여 물리적으로 같은 곳에 있지 않은 Node들에 배포됩니다.

Node

Node는 Cluster를 구성하는 인스턴스의 단위입니다. Cluster는 안정성을 위해 같은 데이터를 여러 노드에 나눠서 저장합니다.

Shard

ScyllaDB를 공부하면서 놀랐던 것이 데이터를 노드 단위로 관리하는 것에서 더 나아서 CPU Core 단위로 관리한다는 것입니다. 특정 CPU에 RAM과 저장공간, 노드의 데이터를 나누어 할당하여 Shard를 생성합니다. Shard는 아무것도 공유하지 않고 독립적으로 작동하는데 이것이 Lock의 필요성을 크게 줄여준다고 합니다.

각 CPU 별로 Memory를 할당하기에 일반적인 차단이나 Memory Lock을 피할 수 있도록 합니다.

S cylla’s data model has led to it being called a “wide column” database, though we sometimes refer to it as a “key-key-value” database to reflect the partitioning and clustering keys.
Reading the article I can understand that the problem was your lacking experience and not Firebase…
By: Giovanni Arixi
Tags: Development, NoSQL, Technology

Reading the article I can understand that the problem was your lacking experience and not Firebase itself.

If you have choosen another nosql like mongo you had the same problems
RDBMS & NoSQL Database Scaling
By: İsmail Gök
Tags: Vertical Scaling, Rdbms, Database Scalability, Horizontal Scaling, NoSQL

It is time to examine both scaling concepts and techniques further for both SQL and NoSQL databases.

Scaling SQL Database Systems

The Relational Databases by their very nature strictly follow the ACID properties. (You can find further information about ACID here: https://en.wikipedia.org/wiki/ACID)

In computer science, ACID (atomicity, consistency, isolation, durability) is a set of properties of database transactions intended to guarantee data validity despite errors, power failures, and other mishaps. In the context of databases, a sequence of database operations that satisfies the ACID properties (which can be perceived as a single logical operation on the data) is called a transaction. For example, a transfer of funds from one bank account to another, even involving multiple changes such as debiting one account and crediting another, is a single transaction.

The power of RDBMS’s comes from making relations between tables and always stay consistent. Hence(keeping ACID rules in mind) RDBMS’s are mostly scaled vertically. (More traffic equals bigger server!)

That does not mean that you cannot scale RDBMS’s horizontally. In order to perform horizontal scaling RDBMS’s are replicated with a method called Master-Slave Replication. Multiple Slave replicas has one master node. The true data is kept at the master node, thus writing only occurs there. The master performs and logs the writes and then passes the updated information to the slaves(replicas). Each slave node outputs a message stating that it has received the update successfully, thus allowing the sending of subsequent updates. Slave nodes can perform read actions any time to reduce the load on the master node. When the master node is down due to a failure, one of the slave nodes become the master node.

While the SQL database servers can scale horizontally like above, the tables can be scaled across those nodes as well. This operation is called Partitioning.

Partitioning is the database process where very large tables are divided into multiple smaller parts. By splitting a large table into smaller, individual tables, queries that access only a fraction of the data can run faster because there is less data to scan. -www.sqlhack.com

Vertical Partitioning

Vertical partitioning is a kind of partitioning that divides a table vertically. You divide a table logically and can access that specific part at once. It can be used in such scenarios when you don’t need to access all the data of a table.

Horizontal Partitioning (Sharding)

Horizontal partitioning is a kind of partitioning that divides tables horizontally. Horizontal partitioning divides a table into multiple tables that contain the same number of columns, but fewer rows.

For example, let’s say there is a big company data ordered by timestamps and the data is used for some analytical algorithm. If the data is commonly retrieved by its year, then it can easily be partitioned into more tables by years.
Why NoSQL?
By: Oleg Stadnichenko
Tags: NoSQL, Architecture, Software Development

Today NoSQL databases are one of the most interesting topics. Sometimes people think that those databases are the best solution ever and could fix all their problems. When you need consistency or data isn’t very huge then you need a relational database. But when you need scalability, distributing and availability then you need NoSQL — this isn’t entirely the true. Let’s find out the difference between NoSQL and SQL databases.

We’ll take into consideration one example of the NoSQL database — document-oriented like MongoDB.

Relational vs non-relational

By term “SQL Database” we usually mean RDBMS(Relational DataBase Management System). The main word here is relational. This is tightly connected with the term “Normal Form”.

In SQL databases your data spread among different tables, to receive information, you must join tables to receive the result. Let’s have a look at two tables below:

Table Client

+----+------+--------+

| Id | Name | phone |

+----+------+--------+

| 1 | Nick | 800081 |

| 2 | Bob | 700071 |

+----+------+--------+

Table Order

+----+-----------+------------+-------+

| Id | Client_Id | Name | Price |

+----+-----------+------------+-------+

| 1 | 1 | "HDD" | 100 |

| 2 | 1 | "SSD" | 200 |

| 3 | 2 | "Computer" | 500 |

+----+-----------+------------+-------+

to find all the orders with the client name you need to join these two tables. Join operation is very expensive.

But if you have a look at one example of NoSQL, document-oriented. Data could be stored in JSON format:

[

{

id: 1

value: {

name: "Nick",

phone: "800081"

order: [{name: "HDD", price: 100}, {name: "SSD", price: 200}]

}

},

{

id: 1

value: {

name: "Nick",

phone: "800081"

order:[ {name: "Computer", price: 500}]

}

}

]

As you can see all the information is stored within one object. Therefore it’s cheaper to get this data for the database because it doesn’t require join operation.

Changing a schema

Another difference is changing a schema. In the relational database you need to apply DDL(Data definition language), e.g. to add a new column. It could look like this:

alter table Client add column email varchar(500);

In the current NoSQL you don’t need to do anything, just insert a new object with a new property.

Overall it isn’t true, you can add schema validation on NoSQL. And if the value isn’t empty you should apply an additional operation on SQL and NoSQL.

Scaling

NoSQL databases mostly have built-in horizontal partitioning. It’s good for availability, but you’ll have problems with consistency.

For SQL databases there is no absolute scaling because it means you could break relations or consistency. And scaled SQL databases mostly are very expensive solutions.

Consistency

If ACID is a requirement for the SQL databases NoSQL hasn’t consistency like in SQL because it’s distributed. Depending on your configuration you could wait for the operation to be consistent on all the nodes. Or you could wait until data inserted in one node and then database will make eventual consistency. You should take this into account when you architect your system.
Introduction to Amazon DynamoDB
By: Nitin Mathew
Tags: Cloud, Guide, AWS, Dynamodb, NoSQL

Amazon Web Services

Introduction to Amazon DynamoDB

Photo by Christopher Gower on Unsplash

What is DynamoDB?

As said by AWS, “Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. Its flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad-tech, IoT, and many other applications.”

DynamoDB is fully managed which means that all the dirty work like operating, scaling, and software patching happens behind the scenes. So as developers, we only have to worry about developing technological solutions that make use of the NoSQL database offered by AWS.

We are going to discuss:

Creating tables Adding & deleting items Querying items Deleting tables

For the purposes of demonstration, we will create a table to store basketball player data.

Creating Tables

In the AWS Management Console, click Services, then click DynamoDB. Click Create table. Enter Table name as BasketballPlayer. The primary key is made up of a partition key and an optional sort key. This is used to uniquely identify an item in the table. Let’s add Partition Key as PlayerId and change the type to Number. The sort key allows for searching within a partition. We won’t use a sort key for our example. Click Create.

Adding & Deleting Items

We are going to manually add and remove items(rows) to the BasketballPlayer table we just created.

Click the Items tab. Click on Create item. Insert value as 1213. Let’s click the + then Append of type String to add a field PlayerName and value Kobe Bryant. Let’s follow the same process to add a Number type with field name JerseyNo and value 24. Click Save. Let’s add another player with PlayerId 1321, PlayerName as Larry Bird, and Height as 2.06. We won’t be adding a JerseyNo this time. These items are easily modifiable if you want to edit the values. To delete the Kobe Bryant entry, select the grey box next on the left of the entry and it changes to blue. Click on Actions and then Delete. Select Delete.

Querying Items

You can add a few more items to test out querying.

While in the Items tab, select the dropdown saying “Scan” and select Query. To query by PlayerId, enter value as 1321. To query by more attributes(columns), click the Add filter button and insert the respective attribute values.

If you’re wondering what the difference between scan and query is, scan searches through the entire table and can take some time for larger tables and a query operation finds items based on Primary Key and optionally Sort Key quickly.

Deleting A Table

Click Delete table on the top-left. Type delete into the input box and click Delete.

It’s that simple.
Lessons learnt on NOSQL and why we moved away from it
By: Sumanth N.S.
Tags: Sql Vs Nosql, Rds, Dynamodb, NoSQL, Sql

In the project that I am working on, recently we took a decision to move away from a NOSQL datastore, AWS Dynamodb. To explain why, I need to talk about the premise on which the DynamoDb was chosen to begin with.

The application was about managing a business entity called a Form . You can imagine it as a json blob with key-value pair, with every key representing a field in a form, henceforth referred as a FormField , which contains the value of the field along with its properties like color, font and fontSize.

Json representation of a Form

The following points were considered to chose a NOSQL datastore for this application (and Dynamodb subsequently)
MongoDB Üzerinde Toplu Insert-Upsert-Merge-Delete Operasyonları
By: İlker Güldalı
Tags: Mongodb Tutorial, Database, Türkçe, Mongodb, NoSQL

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Redis .Net Core Entegrasyonu. Redis (Remote Dictionary Server), açık…
Tags: Net Core, Redis, Caching, Türkçe, NoSQL

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公職-資料處理(含概要)講重點part1
By: Chris Chang
Tags: 張逸, NoSQL, 資料處理

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Tutorial MongoDB (2021). Panduan lengkap belajar MongoDB.
By: Yogiokto Agae
Tags: Pemrograman, Database, Mongodb, NoSQL, Tutorial

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Flutter Integration with Hive(No-Sql)
By: Sajith Vijesekara
Tags: Offline First, Flutter, Setup Guide, Hive, NoSQL

flutter hive integration

Past couple of weeks I have studied flutter development. What I feel Flutter is more cooler than any other mobile development frameworks. So When I deep learn the widgets & API integration I thought to build offline first mobile application.

Setup

Download following dependencies to flutter project.

hive: ^1.4.4+1

path_provider: ^1.6.24

hive_flutter: ^0.3.1

And need to Add These Two As Dev Dependencies.

hive_generator: ^0.7.0+2

build_runner: ^1.8.0

Initialize the Hive database in Application Main Method.

void main() async {

await Hive.initFlutter();

runApp(MyApp());

}

What We are going to do is save User Object to Hive Database. First need to Create Object class.

import 'package:hive/hive.dart';

part 'user-model.g.dart';



@HiveType(typeId: 1)

class User {

@HiveField(0)

final String id;



@HiveField(1)

final String name;



@HiveField(1)

final int age;



User({this.id, this.name, this.age});

}

Note : When Working with Hive database We have to write Adapter class for Each Object to do operations in hive database. But It is very tedious process & hard to write Adapters. For That one We have to use hive_generator . When we put part ‘user-model.g.dart’; & run following command It will Generate Adapter class for User Object. This will generate Adapter class name as “user-model.g.dart”

flutter pub run build_runner build

And We have to Register Generated Adapter in Main Method.

void main() async {

await Hive.initFlutter();

Hive.registerAdapter(UserAdapter());

runApp(MyApp());

}

CRUD Operations

First need to Open Box for Adding Items

Future openBox() async {

var directory = await getApplicationDocumentsDirectory();

Hive.init(directory.path);

box = await Hive.openBox('users');

return;

}

1.Save Data

Future addData(List<User> allLocations) async {

await box.clear();

for (Location u in allLocations) {

box.put(u.id, u);

}

}

2. Retrieve Data

Future<List> _getAllUsers() async {

await openBox();

return box.toMap().values.toList();

}

And That is all . It is simple & fast . Our Next article we will cover how to write offline first Application with hive & REST API.
DynamoDB Design Patterns for Single Table Design
By: Marko, Serverless Life
Tags: AWS, Database, Serverless, Dynamodb, NoSQL

Designing DynamoDB data models with single table design patterns can unlock its potential of unlimited scalability and performance for a very low price.

DynamoDB is the beast that combined with the right design patterns unlocks the potential of unlimited scalability, performance, and low price. However, designing DynamoDB data models can be tricky. Its feature set is limited, but with the correct design patterns, mainly based on prevailed single table design, you can cover almost all use cases that are expected from an OLTP system.

There are multiple resources about designing DynamoDB that did not exist a few years ago. However, I still could not find a short and concise list of design patterns, hence the need for this article. The intention here is not to explain in detail how DynamoDB works, but please see the resources section for more information if needed.

RDBMS databases (SQL databases) were designed at a time when data storage was expensive but processing power was relatively cheap. You save costs with data normalization (removing duplicated data, etc.). But when reading the data, you need to denormalize. This normalization and denormalization require computing power. The only way to scale up the RDBMS database, except with sharding and replication, is vertical, putting it in a larger machine.

Nowadays, we store incomparably more data. Storage is cheap. Correlating to data-size processing power is expensive. With a lot of data, vertical scaling is no longer an option. You have to split data and load it onto multiple computers. That is why we needed a paradigm shift from RDBMS databases. That came with the key-value store and document databases as a variant of NoSQL databases. DynamoDB is one of the most established solutions in that space.

DynamoDB is a hyper scalable, performant, and afordable managed NoSQL database. It should be the first choice for serverless and all solutions that demand scalability. However, because of scalability requirements, like all NoSQL databases, it lacks features common in RDBMS databases. Designing data models is quite difficult and goes against established principles of designing RDBMS databases. That is why it is even more difficult for beginners.

DynamoDB also has fewer features than some other NoSQL databases. That is for a reason. It provides only features that are scalable, in contrast to other databases like MongoDB, which is feature richer.

Continue reading…
Ordering and sorting the posts or data using timestamps in Nosql databases
Tags: Firestore, Timestamp, Firebase, NoSQL, JavaScript

when we are using nosql databases like firestore etc, if you are using api requests like get,post,update,delete. the data will be stored in random order.

There are some couple of queries to setup in backend itself to order or sort the data but if it is not working due to some reasons or issues, here i can teach you how to setup in frontend javascript itself very easily.

Code:-

//store your data in array let say "alldata" for(let obj in alldata)

{

let result = new Date(0); result.setSeconds(alldata[obj].timestamp.seconds); result.setMilliseconds(alldata[obj].timestamp.nanoseconds/1000000); // store the "result" in the array using javascript object alldata[obj].ist=result

}

Below sort the alldata using javascript sort keyword Don't afraid of how to get a,b from your alldata.

Alldata is consists of somany objects.

Each object has different properties like name,ist etc.

From that we are selecting first two objects.

Then next two objects so on in an array (alldata).....

alldata.sort(function(a,b){ return (b.ist).getTime() — (a.ist).getTime() })

Summary:-

I am using firestore backend, it will store default in seconds and nano seconds any current timestamp because due to some issues i was unable to store.

So in array (alldata), i have already seconds and nano seconds just i converted into milliseconds because javascript won’t support nanoseconds then i sort using sort keyword.

I hope you will understood, In other cases if your array doesnot have any seconds and nano seconds, so using post request store the timestamp and using get request sort the data in the javascript frontend and more you can find in w3schools….
DynamoDB: NoSQL gerenciado da AWS
By: Guilherme Milagre
Tags: Tecnologia, AWS, Amazon Dynamodb, Dynamodb, NoSQL

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MongoDB：Capped Collection
Tags: Mongo, Mongodb, NoSQL

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MongoDB Temel Komutlar
By: Hasan Tatarlı
Tags: Database Administration, Basic Comments, Mongodb, NoSQL, Temel Komutlar

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ElasticSearch的Span Near
Tags: Elasticsearch, NoSQL

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NoSQL ve MongoDB Nedir? Nasıl Kurulur?
By: Hasan Tatarlı
Tags: Database Administration, Database, Mongodb, NoSQL, Installation

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Amazon DynamoDB Overview
Tags: Database, Amazon, Dynamodb, Amazon Web Services, NoSQL

Steps to Create Our First DynamoDB Table

First we create a table called users as an example, which the primary key is username.

You will then be directed to the table overview page.

Click Items to create items with JSON format into the table users:

Similarly, add more items to the table

Items tab will show all the contents you have added to. The hobbies attribute which added as List format with two items inside will be displayed as DynamoDB JSON format

To adjust the cost, go to Capacity tab to edit the Read & Write capacity units. Here I will only use 1 for minimizing the cost.
NoSQL資料庫設計概念導讀
By: Liu Cheng Lee
Tags: NoSQL

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Trendyol Favorites: How did we migrate from GraphDB to NoSQL?
By: Emre Tanriverdi
Tags: Graphdb, Scalability, Software Development, NoSQL, Programming

Trendyol Favorites: How did we migrate from GraphDB to NoSQL?

“Technology is the driver, ecommerce is the outcome.”

Favorites in Trendyol, most people in Turkey have either used it or heard it.

We’ve stopped using GraphDB and transformed our datasource to NoSQL (Couchbase) without losing essential features. We wanted to share our experiences and tell you why and how we did it.

Let’s first start with our legacy design:

MATCH x=(:User{userId:25251737})-[:FAVORITED]->(:Content) RETURN x LIMIT 10

User and Product relations were in GraphDB connected with FAVORITED relation, and it had a cache on it with Couchbase.

We didn’t have cache here at first, but Favorites domain grew larger by time. Some people did not have any favorites, and querying those people on GraphDB was time consuming and redundant.

Detailed preview of a relation between a User node and a Product (Content) node and its fields

Sure, it looks and sounds good.

However, even though we used cache in front of GraphDB, it still wasn’t good enough for us. Therefore it started our abandoning process.

In this design all queryable data we use in aggregation, filtering and search operations was updated real-time in our graphDB.

Why did we abandon GraphDB?
Monalize — a MongoDB tool for performance issues scanning
By: Sergey Kuyanov
Tags: Golang, DevOps, Database, Mongodb, NoSQL

When we do not use the MongoDB database correctly, we can often face the thing that the server CPU becomes 80% or even busier. This is not very pleasant, and most often people do not understand what the problem is, but simply scaling the server vertically.

Sometimes it is worth looking at the problem from a different angle. In this article we are going to explain how to find the root cause of such issues. And how to do it in an automated way.

The inspiration for this post was the following article:

While reading the ‘Troubleshooting MongoDB 100% CPU load and slow queries’ post, the following question popped up: why don’t we simplify and automate all of these steps? What if we have several different clients with different mongo applications and databases? Should not we just run some ready tool and got the root cause? Therefore, we decided to create a very simple and small tool that will extract the information we need very quickly and without environment settings. And since I just started learning golang, I decided to use it for the tool
Redis & .NET Core kullanımı. Redis’i .NET ile kullanmak için…
By: Enes Baki Si̇rmen
Tags: Net Core, NoSQL, Redis

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