#dynamodb

[govindhtech]

Prefab Cloud Spanner And PostgreSQL: Flexible And Affordable

Prefab’s Cloud Spanner with PostgreSQL: Adaptable, dependable, and reasonably priced for any size

PostgreSQL is a fantastic OLTP database that can serve the same purposes as Redis for real-time access, MongoDB for schema flexibility, and Elastic for data that doesn’t cleanly fit into tables or SQL. It’s like having a Swiss Army knife in the world of databases. PostgreSQL manages everything with elegance, whether you need it for analytics queries or JSON storage. Its transaction integrity is likewise flawless.

NoSQL databases, such as HBase, Cassandra, and DynamoDB, are at the other end of the database spectrum. Unlike PostgreSQL’s adaptability, these databases are notoriously difficult to set up, comprehend, and work with. However, their unlimited scalability compensates for their inflexibility. NoSQL databases are the giants of web-scale databases because they can handle enormous amounts of data and rapid read/write performance.

However, is there a database that can offer both amazing scale and versatility?

It might have it both ways after its experience with Spanner.

Why use the PostgreSQL interface from Spanner?

At Prefab, Google uses dynamic logging, feature flags, and secrets management to help developers ship apps more quickly. To construct essential features, including evaluation charts, that aid in it operations, scaling, and product improvement, it employ Cloud Spanner as a data store for its customers’ setups, feature flags, and generated client telemetry.

The following are some of the main features that attracted to Spanner:

99.99% uptime by default (multi-availability zone); if you operate in many regions, you can reach up to 99.999% uptime.

Robust ACID transactions

Scaling horizontally, even for writes

Clients, queries, and schemas in PostgreSQL

To put it another way, Spanner offers the ease of use and portability that make PostgreSQL so alluring, along with the robustness and uptime of a massively replicated database on the scale of Google.

How Spanner is used in Prefab

Because Prefab’s architecture is divided into two sections, it made perfect sense for us to have a separate database for each section. This allowed us to select the most appropriate technology for the task. The two aspects of its architecture are as follows:

Using Google’s software development kits (SDKs), developers can leverage its core Prefab APIs to serve their clients.

Google Cloud clients utilize a web application to monitor and manage their app settings.

In addition to providing incredibly low latency, Google’s feature flag services must be scalable to satisfy the needs of the developers’ downstream clients. With Spanner’s support, Java and the Java virtual machine (JVM) are the ideal options for this high throughput, low latency, and high scalability sector. Although it has a much lower throughput, the user interface (UI) of its program must still enable us to provide features to its clients quickly. It uses PostgreSQL, React, and Ruby on Rails for this section of its architecture.

Spanner in operation

The backend for Google Cloud’s dynamic logging’s volume tracking is one functionality that currently makes use of Cloud Spanner. Its SDK transmits the volume for each log level and logger to Spanner after detecting log requests in its customers’ apps. Then, using the Prefab UI, Google Cloud leverages this information to assist users in determining how many log statements will be output to their log aggregator if they enable logging at different settings.

It need a table with the following shape in order to enable this capture:

CREATE TABLE logger_rollup ( id varchar(36) NOT NULL, start_at timestamptz NOT NULL, end_at timestamptz NOT NULL, project_id bigint NOT NULL, project_env_id bigint NOT NULL, logger_name text NOT NULL, trace_count bigint NOT NULL, debug_count bigint NOT NULL, info_count bigint NOT NULL, warn_count bigint NOT NULL, error_count bigint NOT NULL, fatal_count bigint NOT NULL, created_at spanner.commit_timestamp, client_id bigint, api_key_id bigint, PRIMARY KEY (project_env_id, logger_name, id) );

As clients provide the telemetry for Google Cloud’s dynamic logging, this table scales really quickly and erratically. Yes, a time series database or some clever windowing and data removal techniques might potentially be used for this. However, for the sake of this post, this is a simple method to show how Spanner aids in performance management for a table with a large amount of data.

Get 100X storage with no downtime for ⅓ of the cos

It must duplicate Prefab’s database among several zones during production. Because feature flags and dynamic configuration systems are single points of failure by design, reliability is crucial.

Here, Google adopts a belt and suspenders strategy, but its “belt” is robust with Spanner’s uptime SLA and multi-availability zone replication. You would need to treble the cost of a single instance of PostgreSQL to accomplish this. However, replication and automatic failover are included in Cloud Spanner pricing right out of the box. Additionally, you only pay for the bytes you use, and each node has a ton of storage space up to 10TB with Spanner’s latest improvements. This gives the comparison the following appearance for:

The best practice of having a database instance for each environment can become exorbitantly costly at small scales. This was a problem when I initially looked into Spanner a few years back because the least instance size was 1,000 PUs, or one node. Spanner’s scale has since been modified to scale down to less than a whole node, which makes our selection much simpler. Additionally, it allows us to scale up anytime we need to without having to restructure our apps or deal with outages.

Recent enhancements to the Google Cloud ecosystem with Spanner

When we first started using the PostgreSQL interface for Spanner, we encountered several difficulties. Nonetheless, we are thrilled that the majority of the first issues we ran into have been resolved because Google Cloud is always developing and enhancing its goods and services.

Here are a few of our favorite updates:

Query editor: Having a query editor in the Google Cloud console is quite handy as it enables us to examine and optimize any queries that perform poorly.

Key Visualizer: Understanding row keys becomes crucial when examining large-volume NoSQL databases with HBase. It can identify typical problems that lead to hotspots and examine Cloud Spanner data access trends over time with the Key Visualizer.

In brief

Although it has extensive prior experience with HBase and PostgreSQL, it is quite with its choice to use Spanner as Prefab’s preferred horizontally scalable operational database. For its requirements, it has found it to be simple to use, offering all the same scaling capabilities as HBase without the hassles of developing it yourself. It saves time and money when there are fewer possible points of failure and fewer items to manage.

Consider broadening your horizons if you’re afraid of large tables but haven’t explored options other than PostgreSQL. Spanner’s PostgreSQL interface combines the dependable and scalable nature of Cloud Spanner and Google Cloud with the portability and user-friendliness of PostgreSQL.

Start Now

Spanner is available for free for the first ninety days or for as low as $65 a month after that. Additionally, it would be delighted to establish a connection with you and would appreciate it if you could learn more about its Feature Flags, Dynamic Logging, and Secret Management, which are components of the solution built on top of Cloud Spanner.

Read more on Govindhtech.com

[dgruploads]

Master AWS DynamoDB : 10 essential interview questions with answers on AWS DynamoDB!

[devsnews]

This article will cover how to store data as files using Amazon S3.

[jaiinfoway]

Visit #jainfoway www.jaiinfoway.com for How to build and deploy serverless applications on AWS

Read more; https://jaiinfoway.com/how-to-build-and-deploy-serverless-applications-on-aws/

[asm4g]

AWS batch에 관한 생각들

많은 양의 자료를 여러 대의 컴퓨터를 사용해서 처리해야 할 때 어떻게 하는 ���이 효율적일지를 생각해 보자. 지금 업무와 관련해서 문제를 단순화 시키고 비슷한 유사 상황을 만들어 이야기해 보자. 우선 레이블을 가진 8,000개 정도의 비디오를 처리해야 한다. 중요한 것은 컴퓨팅 리소스를 아끼기 위해 처리된 상황을 기록하는 데이터베이스를 준비하는 것이다. 이 데이터 베이스는 처리하는 "상황"에 관한 항목을 가지고 있어야 하고 필요한 "입력자료"에 관한 항목이 있어야 하고 처리하는 "알고리즘"에 관한 항목이 있어야 한다. DynamoDB와 같은 비관계형 데이터 베이스를 이용할 경우 이러한 내용들을 모두 한번에 넣어 둘 수가 있다. 다만, 어떻게 필요한 내용들을 찾아 내고 관련된 계산들을 할 수 있을지 미리 생각해 두어야 한다. 또한 이 모든 일들이 자동적으로 일어나도록 설계해야 한다. 예를 들어, 원하는 ID의 자료들을 AWS S3에 올려 놓으면 자동적으로 필요한 일들이 이루어져서 마지막 결과물이 생성되는 식이다. 또한 이 과정에서 불필요한 작업의 반복을 줄여야 하고 중간에 작업이 멈추더라도 마지막 상황에 이어서 작업이 계속 될 수 있어야 한다. 또한 중간에 오류가 나더라도 작업은 끊임없이 계속되며, 나중에 개별 수정을 할 경우 오류를 고친 이후에 다시 작업을 반복해서 끝낼수 있어야 한다. NC에 이어서 SC도 마지막으로 해야할 일들은 비슷하다. 이참에 continuous pipeline에 대한 개념들을 정립해 보도록 하자.

[practicallogix]

DynamoDB: A NoSQL Powerhouse for Modern Applications

In the realm of big data and rapidly evolving digital products, relational databases often face challenges in meeting the demands for flexibility, scalability, and speed. This is where NoSQL databases become relevant, offering an alternative to traditional SQL databases through dynamic, schema-less data management options. Among the most prominent and powerful NoSQL solutions available today is Amazon DynamoDB. As a fully managed, serverless NoSQL database, DynamoDB provides exceptional scalability, performance, and flexibility for modern applications.

In this blog post, we will examine the characteristics that define DynamoDB as a NoSQL database, its operational mechanisms, and the reasons it is an essential choice for businesses seeking a high-performance, reliable data solution.

What is NoSQL?

NoSQL, an abbreviation for "Not Only SQL," refers to a class of databases that diverge from the traditional relational model, which organizes data in rows and columns with predefined schemas. NoSQL databases offer flexible data storage alternatives, such as key-value pairs, documents, graphs, or wide columns. This adaptability makes them particularly well-suited for managing unstructured or semi-structured data, processing large volumes of information, and facilitating horizontal scaling to meet the requirements of modern applications.

Unlike SQL databases, which excel in handling structured data and complex queries, NoSQL databases emphasize flexibility and scalability. They empower developers to modify data models on the fly, support large-scale distributed systems, and cater to real-time applications that necessitate rapid access to data.

DynamoDB as a NoSQL Database

Amazon DynamoDB is recognized as one of the most popular NoSQL databases in the cloud, celebrated for its scalability, performance, and fully managed nature. Developed by Amazon Web Services (AWS), DynamoDB is engineered to support both key-value and document-based data models, offering versatility for a wide array of use cases.

Key Features of DynamoDB as a NoSQL Database

1. Schema-Less Data Model

At the heart of its NoSQL architecture, DynamoDB enables a schema-less data model. This feature allows each item in a DynamoDB table to have a unique set of attributes, providing significant flexibility in how data is stored and structured. This contrasts sharply with relational databases, which impose strict schemas with predefined columns and data types.

For instance, in a DynamoDB table storing user information, one item may include a user’s name, email, and age, while another might contain only a name and address. This flexibility is crucial for applications that manage dynamic and evolving data structures, such as social media platforms or IoT applications.

2. High Scalability

DynamoDB is designed to be horizontally scalable, enabling it to expand its storage and compute capacity by adding additional servers rather than relying on a single server, as is the case with traditional SQL databases. This capacity for horizontal scaling allows DynamoDB to effectively manage substantial amounts of data and traffic.

DynamoDB automatically adjusts its capacity up or down in response to your application’s needs, ensuring consistent performance even during traffic surges. Whether handling hundreds or millions of requests per second, DynamoDB dynamically modifies its read and write capacity, making it an ideal solution for applications requiring both elasticity and reliability.

3. Distributed Architecture

A defining characteristic of NoSQL databases is their distributed nature, and DynamoDB exemplifies this feature. DynamoDB distributes data across multiple servers to guarantee high availability and fault tolerance. This architecture ensures that if one server encounters an issue, data can still be accessed from another server, thereby minimizing downtime and ensuring business continuity.

Furthermore, with Global Tables, DynamoDB facilitates data replication across multiple AWS regions, ensuring low-latency access for users around the globe. This global replication is vital for businesses serving a worldwide audience, offering a seamless user experience regardless of location.

4. Low Latency and High Performance

DynamoDB is optimized for low-latency, high-performance workloads. It consistently delivers single-digit millisecond response times, even as data volume and traffic levels rise. For applications such as real-time gaming, mobile applications, or e-commerce, where rapid data access is critical, DynamoDB ensures reliable and speedy performance.

For read-intensive workloads, DynamoDB Accelerator (DAX) is available to further enhance performance. DAX serves as an in-memory caching service that reduces response times from milliseconds to microseconds, making it particularly suitable for applications that demand real-time, lightning-fast data access.

DynamoDB Use Cases

DynamoDB’s flexibility, scalability, and low-latency performance position it as an ideal solution for a diverse range of applications. Notable use cases include:

E-commerce and Retail: DynamoDB effectively manages product catalogs, user sessions, shopping carts, and order histories, ensuring swift and reliable performance, even during peak traffic periods such as Black Friday.

Mobile and Web Applications: DynamoDB is capable of storing user profiles, activity logs, and other data for real-time applications that require high throughput and low-latency access.

Gaming Backends: With its capacity for rapid scaling and real-time data handling, DynamoDB is particularly suited for multiplayer gaming backends, where consistent performance and availability are essential.

IoT (Internet of Things): IoT applications frequently generate vast amounts of data from sensors and devices. DynamoDB is designed to manage this data efficiently, enabling IoT systems to scale seamlessly as additional devices are connected.

Conclusion 

Dynamodb is nosql stands as a leading NoSQL solution, providing the flexibility, scalability, and performance essential for supporting modern, data-driven applications. Whether developing an e-commerce platform, real-time analytics solution, or mobile app, DynamoDB's serverless architecture and schema-less data model facilitate efficient data storage, access, and management with minimal overhead. 

By opting for DynamoDB, you can ensure your application is well-equipped to manage large-scale, high-velocity workloads while benefiting from a fully managed, secure, and highly available NoSQL database.

[lucid-outsourcing-solutions]

Managing ColdFusion Data with AWS DynamoDB: NoSQL Database Integration

[govindhtech]

Amazon DynamoDB: A Complete Guide To NoSQL Databases

Amazon DynamoDB fully managed, serverless, NoSQL database has single-digit millisecond speed at any scale.

What is Amazon DynamoDB?

You can create contemporary applications at any size with DynamoDB, a serverless NoSQL database service. Amazon DynamoDB is a serverless database that scales to zero, has no cold starts, no version upgrades, no maintenance periods, no patching, and no downtime maintenance. You just pay for what you use. A wide range of security controls and compliance criteria are available with DynamoDB. DynamoDB Global Tables is a multi-region, multi-active database with a 99.999% availability SLA and enhanced resilience for globally dispersed applications. Point-in-time recovery, automated backups, and other features support DynamoDB dependability. You may create serverless event-driven applications with Amazon DynamoDB streams.

Use cases

Create software programs

Create internet-scale apps that enable caches and user-content metadata, which call for high concurrency and connections to handle millions of requests per second and millions of users.

Establish media metadata repositories

Reduce latency with multi-Region replication between AWS Regions and scale throughput and concurrency for media and entertainment workloads including interactive content and real-time video streaming.

Provide flawless shopping experiences

When implementing workflow engines, customer profiles, inventory tracking, and shopping carts, use design patterns. Amazon DynamoDB can process millions of queries per second and enables events with extraordinary scale and heavy traffic.

Large-scale gaming systems

With no operational overhead, concentrate on promoting innovation. Provide player information, session history, and leaderboards for millions of users at once when developing your gaming platform.

Amazon DynamoDB features

Serverless

You don’t have to provision any servers, patch, administer, install, maintain, or run any software when using Amazon DynamoDB. DynamoDB offers maintenance with no downtime. There are no maintenance windows or major, minor, or patch versions.

You only pay for what you use using DynamoDB’s on-demand capacity mode, which offers pay-as-you-go pricing for read and write requests. With on-demand, DynamoDB maintains performance with no management and quickly scales up or down your tables to accommodate capacity. Additionally, when there is no traffic or cold starts at your table, it scales down to zero, saving you money on throughput.

Amazon DynamoDB NoSQL

NoSQL

DynamoDB is a NoSQL database that outperforms relational databases in performance, scalability, management, and customization. DynamoDB supports several use cases with document and key-value data types.

DynamoDB does not offer a JOIN operator, in contrast to relational databases. To cut down on database round trips and the amount of processing power required to respond to queries, advise you to denormalize your data model. DynamoDB is a NoSQL database that offers enterprise-grade applications excellent read consistency and ACID transactions.

Fully managed

DynamoDB is a fully managed database service that lets you focus on creating value to your clients. It handles hardware provisioning, security, backups, monitoring, high availability, setup, configurations, and more. This guarantees that a DynamoDB table is immediately prepared for production workloads upon creation. Without the need for updates or downtime, Amazon DynamoDB continuously enhances its functionality, security, performance, availability, and dependability.

Single-digit millisecond performance at any scale

DynamoDB was specifically designed to enhance relational databases’ scalability and speed, achieving single-digit millisecond performance at any scale. DynamoDB is designed for high-performance applications and offers APIs that promote effective database utilization in order to achieve this scale and performance. It leaves out aspects like JOIN operations that are ineffective and do not function well at scale. Whether you have 100 or 100 million users, DynamoDB consistently provides single-digit millisecond performance for your application.

What is a DynamoDB Database?

Few people outside of Amazon are aware of the precise nature of this database. Although the cloud-native database architecture is private and closed-source, there is a development version called DynamoDB Local that is utilized on developer laptops and is written in Java.

You don’t provision particular machines or allot fixed disk sizes when you set up DynamoDB on Amazon Web Services. Instead, you design the database according to the capacity that has been supplied, which includes the number of transactions and kilobytes of traffic that you want to accommodate per second. A service level of read capacity units (RCUs) and write capacity units (WCUs) is specified by users.

As previously mentioned, users often don’t call the Amazon DynamoDB API directly. Rather, their application will incorporate an Amazon Web Services, which will manage the back-end interactions with the server.

Denormalization of DynamoDB data modeling is required. Rethinking their data model is a difficult but manageable step for engineers accustomed to working with both SQL and NoSQL databases.

Read more on govindhtech.com

[akrnd085]

Boto3 and DynamoDB: Integrating AWS’s NoSQL Service with Python

[truepdf]

The DynamoDB Book https://inchighal.com/product/the-dynamodb-book/

#DynamoDB #NoSQL #Database #AWS #CloudComputing #WebDevelopment #Serverless #DataManagement #TechTalk #Programming #BackEnd #AmazonDynamoDB #DeveloperLife

[antstackinc]

AWS DynamoDB vs GCP BigTable| AntStack

Data is a precious resource in today’s fast-paced world, and it’s increasingly stored in the cloud for its benefits of accessibility, scalability, and, most importantly, security. As data volumes grow, individuals and businesses can easily expand their cloud storage without investing in new hardware or infrastructure. In the modern context, the answer to data storage often boils down to the cloud, but the choice between cloud services like AWS DynamoDB and GCP BigTable remains crucial.

[onetechavenue]

Altoros Releases 2023 NoSQL DBaaS Performance Report: Couchbase Capella vs. Amazon DynamoDB vs. MongoDB Atlas vs. Redis Enterprise Cloud

PHILIPPINES — Altoros, a consultancy focusing on research and development for Global 2000 organizations, today announced the results of its latest performance benchmark report, commissioned by cloud database platform company Couchbase. The study provides a comparative analysis of the performance of four NoSQL cloud databases: Couchbase CapellaTM, Amazon DynamoDB, MongoDB Atlas, and Redis…

[muellermh]

Welches sind die am besten geeigneten Tools & Frameworks zur Entwicklung von AWS-Cloud-Computing-Anwendungen?: "Entwicklung von AWS-Cloud-Anwendungen: Die besten Tools & Frameworks von MHM Digitale Lösungen UG"

#AWS #CloudComputing #AWSLambda #AWSEC2 #ServerlessComputing #AmazonEC2ContainerService #AWSElasticBeanstalk #AmazonS3 #AmazonRedshift #AmazonDynamoDB

In der heutigen digitalen Welt ist Cloud-Computing ein Schlüsselthema, vor allem bei aufstrebenden Unternehmen. AWS (Amazon Web Services) ist der weltweit führende Cloud-Computing-Anbieter und bietet eine breite Palette an Tools und Frameworks, die Entwicklern dabei helfen, schneller und effizienter zu arbeiten. In diesem Artikel werden die besten Tools und Frameworks erörtert, die für die…

[cittasolutions]

Hire a Dedicated DynamoDB Developer Citta professional DynamoDB database designer understands how to create a safe database that works well with your application and transfers data effortlessly from and to your application.