From Oracle to Databases for AI: The Evolution of Data Storage
KDnuggets
FEBRUARY 15, 2022
From Oracle, to NoSQL databases, and beyond, read about data management solutions from the early days of the RBDMS to those supporting AI applications.
RDBMS vs NoSQL: Key Differences and Similarities
Knowledge Hut
MARCH 15, 2024
Making decisions in the database space requires deciding between RDBMS (Relational Database Management System) and NoSQL, each of which has unique features. RDBMS uses SQL to organize data into structured tables, whereas NoSQL is more flexible and can handle a wider range of data types because of its dynamic schemas.
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NoSQL vs SQL- 4 Reasons Why NoSQL is better for Big Data applications
ProjectPro
MARCH 19, 2015
Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.
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HBase vs Cassandra-The Battle of the Best NoSQL Databases
ProjectPro
SEPTEMBER 16, 2021
NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.
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Big Data Technologies that Everyone Should Know in 2024
Knowledge Hut
APRIL 25, 2024
Each of these technologies has its own strengths and weaknesses, but all of them can be used to gain insights from large data sets. As organizations continue to generate more and more data, big data technologies will become increasingly essential. Let's explore the technologies available for big data.
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CockroachDB In Depth with Peter Mattis - Episode 35
Data Engineering Podcast
JUNE 10, 2018
Summary With the increased ease of gaining access to servers in data centers across the world has come the need for supporting globally distributed data storage. With the first wave of cloud era databases the ability to replicate information geographically came at the expense of transactions and familiar query languages.
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Graph Databases In Production At Scale Using DGraph with Manish Jain - Episode 44
Data Engineering Podcast
AUGUST 19, 2018
There are a few ways that graph structures and properties can be implemented, including the ability to store data in the vertices connecting nodes and the structures that can be contained within the nodes themselves. How does the query interface and data storage in DGraph differ from other options?
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100 Unpacking Fauna: A Global Scale Cloud Native Database
Data Engineering Podcast
APRIL 22, 2019
Summary One of the biggest challenges for any business trying to grow and reach customers globally is how to scale their data storage. Contact Info @evan on Twitter LinkedIn Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?
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Getting Started with Cloudera Data Platform Operational Database (COD)
Cloudera
NOVEMBER 23, 2021
HBase is a column-oriented data storage architecture that is formed on top of HDFS to overcome its limitations. Although the HBase architecture is a NoSQL database, it eases the process of maintaining data by distributing it evenly across the cluster. Apache HBase.
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Big Data Analytics: How It Works, Tools, and Real-Life Applications
AltexSoft
MAY 14, 2021
A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing. NoSQL databases.
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Most important Data Engineering Concepts and Tools for Data Scientists
DareData
JANUARY 30, 2023
In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.
How to query JSONB array of objects in PostgreSQL
Hevo
DECEMBER 21, 2023
Do you have a NoSQL database that has no rigid shape and is causing data analysis complexity nightmares? PostgreSQL is a high-performing, open-sourced object-relational database with two JSON data storage types, JSON and JSONB. With JSON in PostgreSQL, you can have a solution to your complex problem.
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Hadoop vs Spark: Main Big Data Tools Explained
AltexSoft
JUNE 7, 2021
Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. Data storage options. Hadoop nodes: masters and slaves.
Types of Databases
Grouparoo
DECEMBER 26, 2021
For data storage, the database is one of the fundamental building blocks. As data must conform to a defined structural format, future changes to data that affect the structure will require revision of the entire database to reflect the necessary changes. The format for storing data plays a critical role in this process.
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The Future of Database Management in 2023
Knowledge Hut
JULY 24, 2023
NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.
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A Guide to Data Pipelines (And How to Design One From Scratch)
Striim
SEPTEMBER 11, 2024
Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. Data storage Data storage follows.
Top 16 Data Science Job Roles To Pursue in 2024
Knowledge Hut
DECEMBER 26, 2023
According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. In other words, they develop, maintain, and test Big Data solutions. To become a Big Data Engineer, knowledge of Algorithms and Distributed Computing is also desirable.
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CDC on DynamoDB
Rockset
MAY 10, 2022
DynamoDB is a popular NoSQL database available in AWS. However, DynamoDB, like many other NoSQL databases, is great for scalable data storage and single row retrieval but leaves a lot to be desired when it comes to analytics. With SQL databases, analysts can quickly join, group and search across historical data sets.
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CloudBank’s Journey from Mainframe to Streaming with Confluent Cloud
Confluent
MARCH 4, 2019
A trend often seen in organizations around the world is the adoption of Apache Kafka ® as the backbone for data storage and delivery. As mentioned earlier, companies today need to be able to process not only transactional data but also unstructured data coming from sources like logs.
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Front End vs Back End vs Full Stack
Edureka
JULY 16, 2024
Back-end developers offer mechanisms of server logic APIs and manage databases with SQL or NoSQL technological stacks in PHP, Python, Ruby, or Node. js, React and Angular as the front-end technology stack, Python and Ruby on Rails as the backend technology stack, and SQL or NoSQL as a database architecture.
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Recap of Hadoop News for February 2018
ProjectPro
MARCH 1, 2018
(Source : [link] ) For the complete list of big data companies and their salaries- CLICK HERE How Erasure Coding Changes Hadoop Storage Economics.Datanami.com, February 7, 2018 Erasure coding has been introduced in Hadoop 3.0 that lets users pack up to 50% additional data within the same hadoop cluster.
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Top 12 Backend Developer Skills You Must Know in 2024
Knowledge Hut
APRIL 25, 2024
Create data storage and acceptance solutions for websites, especially those that take payments. Knowledge of Databases When working on a project, you must realize that data storage is essential since they contain a lot of information. Creation and management of application programming interfaces (APIs).
What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools
Monte Carlo
OCTOBER 31, 2024
Proficiency in Programming Languages Knowledge of programming languages is a must for AI data engineers and traditional data engineers alike. In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development.
Difference Between Data Structure and Database
Knowledge Hut
MARCH 27, 2024
Scales efficiently for specific operations within algorithms but may face challenges with large-scale data storage. Database vs Data Structure If you are thinking about how to differentiate database and data structure, let me explain the difference between the two in detail on the parameters mentioned above in the table.
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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform
Cloudera
AUGUST 31, 2021
While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.
Top 10 Real World Applications of Cloud Computing
Knowledge Hut
NOVEMBER 7, 2023
Applications of Cloud Computing in Data Storage and Backup Many computer engineers are continually attempting to improve the process of data backup. Previously, customers stored data on a collection of drives or tapes, which took hours to collect and move to the backup location.
The Role of Database Applications in Modern Business Environments
Knowledge Hut
JULY 26, 2023
It also has strong querying capabilities, including a large number of operators and indexes that allow for quick data retrieval and analysis. Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases. Spatial Database (e.g.-
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5 Layers of Data Lakehouse Architecture Explained
Monte Carlo
JANUARY 5, 2024
This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Storage layer The storage layer in data lakehouse architecture is–you guessed it–the layer that stores the ingested data in low-cost stores, like Amazon S3.
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Data Lakehouse Architecture Explained: 5 Layers
Monte Carlo
JANUARY 5, 2024
This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Storage layer The storage layer in data lakehouse architecture is–you guessed it–the layer that stores the ingested data in low-cost stores, like Amazon S3.
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Top 10 Hadoop Tools to Learn in Big Data Career 2024
Knowledge Hut
DECEMBER 21, 2023
NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. NoSQL databases can handle node failures. Different databases have different patterns of data storage. Cons : In Avro, the schema is required to read and write data.
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DataOps Architecture: 5 Key Components and How to Get Started
Databand.ai
AUGUST 30, 2023
DataOps Architecture Legacy data architectures, which have been widely used for decades, are often characterized by their rigidity and complexity. These systems typically consist of siloed data storage and processing environments, with manual processes and limited collaboration between teams.
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Hive vs.HBase–Different Technologies that work Better Together
ProjectPro
DECEMBER 7, 2016
The complexity of big data systems requires that every technology needs to be used in conjunction with the other. Your Facebook profile data or news feed is something that keeps changing and there is need for a NoSQL database faster than the traditional RDBMS’s. Pinterest uses HBase to store the graph data.
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Introduction to MongoDB for Data Science
Knowledge Hut
NOVEMBER 3, 2023
The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. What is MongoDB for Data Science? Why Use MongoDB for Data Science?
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Data Engineer Roles And Responsibilities 2022
U-Next
AUGUST 17, 2022
Because of this, all businesses—from global leaders like Apple to sole proprietorships—need Data Engineers proficient in SQL. NoSQL – This alternative kind of data storage and processing is gaining popularity. The term “NoSQL” refers to technology that is not dependent on SQL, to put it simply.
MongoDB and Hadoop
ProjectPro
NOVEMBER 5, 2014
Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.
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Data Scientist vs Data Engineer: Differences and Why You Need Both
AltexSoft
OCTOBER 30, 2021
Data engineer’s integral task is building and maintaining data infrastructure — the system managing the flow of data from its source to destination. This typically includes setting up two processes: an ETL pipeline , which moves data, and a data storage (typically, a data warehouse ), where it’s kept.
How to Learn SQL Basics for Data Science in 2023?
ProjectPro
DECEMBER 17, 2021
are shifting towards NoSQL databases gradually as SQL-based databases are incapable of handling big-data requirements. Industry experts at ProjectPro say that although both have been developed for the same task, i.e., data storage, they vary significantly in terms of the audience they cater to.
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Data Engineering Learning Path: A Complete Roadmap
Knowledge Hut
JUNE 23, 2023
Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.
The Good and the Bad of Hadoop Big Data Framework
AltexSoft
JULY 29, 2022
No matter the actual size, each cluster accommodates three functional layers — Hadoop distributed file systems for data storage, Hadoop MapReduce for processing, and Hadoop Yarn for resource management. As a result, today we have a huge ecosystem of interoperable instruments addressing various challenges of Big Data.
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Azure Data Engineer Job Description [Roles and Responsibilities]
Knowledge Hut
SEPTEMBER 25, 2023
As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.
Introducing Netflix’s Key-Value Data Abstraction Layer
Netflix Tech
SEPTEMBER 18, 2024
Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability. The Key-Value Service The KV data abstraction service was introduced to solve the persistent challenges we faced with data access patterns in our distributed databases.
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Top 15 Software Engineer Projects 2023 [Source Code]
Knowledge Hut
OCTOBER 27, 2023
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Top 10 MongoDB Career Options in 2024 [Job Opportunities]
Knowledge Hut
MARCH 22, 2024
Interested in NoSQL databases? MongoDB Careers: Overview MongoDB is one of the leading NoSQL database solutions and generates a lot of demand for experts in different fields. During the era of big data and real-time analytics, businesses face challenges, and the need for skilled MongoDB professionals has grown to an order of magnitude.
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15+ Must Have Data Engineer Skills in 2023
Knowledge Hut
NOVEMBER 28, 2023
Relational database management systems (RDBMS) remain the key to data discovery and reporting, regardless of their location. Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023.
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