This article will explore the key-value store feature, which is less popular, but still plays an integral part in PostgreSQL's NoSQL capabilities.
Key-value stores are essential and often used, especially in operations that require fast and frequent lookups. They allow an object - the key - to be mapped to another object, the value. This way, the values can easily be retrieved, by looking up the key.
In Java, the most popular
Map implementation is the
HashMap class. Aside from key-value mapping, it’s used in code that requires frequest insertions, updates and lookups. The insert and lookup time is a constant O(1).
In this tutorial, we’ll go over how to get the Keys and Values of a map in Java.
#java #java: how to get keys and values from a map #keys #map #values #how to get keys and values from a map
Category: Tutorials | Tags: Cassandra, Columns, Database, Database Management, Database Structure, DB2, Document Stores, Dynamic Schema, Extensible Record Stores, Graph Stores, JSON, Key-Value, MSSQL, Multi-Row, MySQL, Node, Node Relationship Node, Non-Relational Databases, NoSQL, NoSQL Model, Query, Rows, Scalability, Schema Free, SQL, Stores, Tables, Wide-Column
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A NoSQL or a NoSQL Database is a term used when referring to a “non SQL” or “not only SQL” database. NoSQL databases store data in a different format than a traditional relational database management systems. This is why NoSQL is often associated with the term “non-relational” database. Simply put, NoSQL databases are modern databases with high flexibility, blazing performance, and built for scalability. These databases are used when you require low latency and high extensibility while working with large data structures. The versatility of NoSQL is due to the nature of as being unrestricted in comparison to relational databases models such as MySQL or DB2.
There are multiple differences between SQL and NoSQL database types. In the table below, we will compare some of the most critical variations.
#tutorials #cassandra #columns #database #database management #database structure #db2 #document stores #dynamic schema #extensible record stores #graph stores #json #key-value #mssql #multi-row #mysql #node #node relationship node #non-relational databases #nosql #nosql model #query #rows #scalability #schema free #sql #stores #tables #wide-column
Our testing shows that Azure SQL Database can be used as a highly scalable low latency key-value store. Starting with a cost-efficient 4-core General Purpose database, we see an order of magnitude increase in workload throughput as we increase dataset size by 100x and scale across the spectrum of database SKUs to a Business Critical database with 128 cores, with read and write latency remaining in single-digit milliseconds.
Azure SQL is a relational database, so the title of this blog may come as a surprise. But Azure SQL is also a general-purpose database. The strength of a general-purpose DBMS is in accommodating multiple data models and designs, not all of them necessarily relational, in the same physical database, and still providing robust functionality and sufficiently good performance and scale. To that end, in addition to representing data relationally using tables, columns, and rows, Azure SQL also provides multi-model capabilities, including support for JSON, XML, and Graph data. Regardless of data model, developers can continue using familiar SQL language.
One non-relational data model popular among developers is key-value store. There are many specialized key-value data stores, each with its unique capabilities and strengths. In this blog we will take a closer look at the performance and scalability of Azure SQL Database, when used as a key-value store.
To do that, we will use YCSB, or Yahoo! Cloud Serving Benchmark. To quote from the project Github page, The goal of the YCSB project is to develop a framework and common set of workloads for evaluating the performance of different “key-value” and “cloud” serving stores. YCSB is a mature benchmark. In the last 10 years, it has been used to test well-known NoSQL and key-value data stores, such as Cassandra, MongoDB, Redis, DynamoDB, and many others, over thirty in total. Notably, YCSB also supports JDBC as a generic interface to relational databases. Our YCSB tests used JDBC to talk to Azure SQL.
YCSB provides several canned workloads. For our tests, we chose Workload A in default configuration. This is an update heavy workload with a 50/50 read/write ratio and a uniform distribution of read and write requests across the dataset.
In a relational database, YCSB uses a single table to represent the key-value dataset:
CREATE TABLE usertable ( YCSB_KEY varchar(255) NOT NULL, FIELD0 varchar(100) NOT NULL, FIELD1 varchar(100) NOT NULL, FIELD2 varchar(100) NOT NULL, FIELD3 varchar(100) NOT NULL, FIELD4 varchar(100) NOT NULL, FIELD5 varchar(100) NOT NULL, FIELD6 varchar(100) NOT NULL, FIELD7 varchar(100) NOT NULL, FIELD8 varchar(100) NOT NULL, FIELD9 varchar(100) NOT NULL CONSTRAINT pk_usertable PRIMARY KEY (YCSB_KEY) );
We kept the default YCSB schema with a key column and ten value columns, but used the varchar(100) data type for value columns instead of the default text, which is deprecated in SQL Server.
As the first step before running each test, we used YCSB to load this table with a configurable number of rows. In the generated dataset, each FIELD[N] column contains a string of random 100 characters. With the default workload configuration, each read request is a SELECT query returning one row matching a given YCSB_KEY value, with all columns included in the result set, and each write request is an UPDATE query updating one of FIELD[N] columns for a given YCSB_KEY value. Each test runs as many total operations (requests) as there are rows in the table. With a 50/50 read/write ratio, these total requests are split about equally between SELECT and UPDATE queries.
Single-row requests are common in key-value stores. On one hand, such queries are simple for the query processing engine of a relational database to optimize and execute. Query execution plans we observed were trivial. On the other hand, using single-row queries creates a very chatty workload, with respect to both network and storage traffic. For chatty workloads, higher (when compared to typical latencies in on-premises data centers) network and storage latencies in public cloud may create a performance challenge.
YCSB supports many configuration options for its core workloads, and supports building custom workloads as well. In our testing, we intentionally chose to focus on a more challenging update heavy workload and larger datasets (10 million – 1 billion rows) to determine performance and scalability across the range of Azure SQL Database SKUs.
#azure sql #azuresql #key-value store #performance
Despite the Covid-19 threat to the world and economy of every country, Online Grocery Market has recorded a 3X increase since 2019 till now.
“About 1-4th online shoppers are already shopping groceries on the internet in developed countries and 55% are willing to in near future. – Nielson study”
The new store these days are digital stores, Web stores, and Mobile applications where 70% of the customers reach and buy every day.
Take your store where the customers are to generate more revenue by developing e-commerce grocery store/application and Supermarket online store and mobile application.
Online grocery shopping sales in the United States from 2018 to 2023(in billion U.S. dollars)
“As per Statista, The U.S. online grocery market was estimated to generate sales worth about 28.68 billion U.S. dollars in 2019, with sales forecast to reach 59.5 billion U.S. dollars by 2023.”
Online store and mobile applications are helping small grocery business owners reach 70% more customers and generate unbelievable but real 48% more revenue other than the existing one. Check out a few of the businesses listed below:
Want to start an online grocery store? – Here’s what you should know
If you dream of owning your own online store regardless are you setting up a small business for the first time or you’ve been in the game a long time, this guide will help you learn how to start an online store.
Online selling, better known as e-commerce, has truly hit its pace. Fortunately, getting started is easier than you might think provided you have basic information about the business (which we will cover here) and you have a team of ecommerce website store solution experts to get the things implemented.
Accenture estimates, by the end of 2020, the ecommerce industry will get 13.5% of the revenue share. What does it mean for online store owners? It means that out of every 7 dollars spent on retail consumption: eCommerce will get about 1 dollar.
This article was originally published - How to start an online grocery store?
#start an online grocery store, #steps to opening a successful online business #steps to open online store #create your own grocery store #ecommerce store development