ProjectPro

JUNE 6, 2025

It proposes a simple NoSQL model for storing vast data types, including string, geospatial , binary, arrays, etc. Before we get started on exploring some exciting projects on MongoDB, let’s understand what exactly MongoDB offers as a NoSQL Database. MongoDB stores data in collections of JSON documents in a human-readable format.

MongoDB 66

MongoDB Coding Project NoSQL 66

ProjectPro

JUNE 6, 2025

Looking to master SQL? Begin your SQL journey with confidence! This all-inclusive guide is your roadmap to mastering SQL, encompassing fundamental skills suitable for different experience levels and tailored to specific job roles, including data analyst, business analyst, and data scientist. But why is SQL so essential in 2023?

SQL 40

SQL Relational Database Business Analyst Database 40

ProjectPro

JUNE 6, 2025

Type of Database Softwares Used for Database Management Relational Database MySQL, IBM Db2, Oracle Database, Microsoft SQL Server, PostgreSQL Graph Database Neo4J, Datastax Enterprise Graph Columnar Database HBase, MariaDB, Cassandra, Azure SQL Data Warehouse , Google BigQuery NoSQL Database Apache Cassandra, MongoDB , CouchBase, CouchDB, You don’t (..)

Data Engineering 94

Data Engineering Data Engineer Engineering Amazon Web Services 94

Rockset

JULY 22, 2022

Last week, Rockset hosted a conversation with a few seasoned data architects and data practitioners steeped in NoSQL databases to talk about the current state of NoSQL in 2022 and how data teams should think about it. NoSQL is great for well understood access patterns. Rick Houlihan Where does NoSQL fit in the modern data stack?

NoSQL 52

NoSQL SQL Database MongoDB 52

ProjectPro

JUNE 6, 2025

Access various data resources with the help of tools like SQL and Big Data technologies for building efficient ETL data pipelines. Structured Query Language or SQL (A MUST!!): And one of the most popular tools, which is more popular than Python or R , is SQL. You will work with unstructured data and NoSQL relational databases.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

The following questions, sourced from Glassdoor span topics like SQL queries, Python programming, data storage, data warehousing , and data modeling, providing a comprehensive overview of what to expect in your Amazon Data Engineer interview. What are the key considerations for choosing between relational databases and NoSQL databases on AWS?

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

ProjectPro

JUNE 6, 2025

The relational databases- Amazon Aurora , Amazon Redshift, and Amazon RDS use SQL (Structured Query Language) to work on data saved in tabular formats. Amazon DynamoDB is a NoSQL database that stores data as key-value pairs. NoSQL Document Database. SQL Support Supports SQL queries and transactions.

Amazon Web Services 40

Amazon Web Services NoSQL Relational Database AWS 40

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.

NoSQL 52

NoSQL Database-centric MongoDB Relational Database 52

ProjectPro

JUNE 6, 2025

He is an expert SQL user and is well in both database management and data modeling techniques. On the other hand, a Data Engineer would have similar knowledge of SQL, database management, and modeling but would also balance those out with additional skills drawn from a software engineering background.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

Rockset

JULY 6, 2022

So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data. Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. SQL queries were easier to write. They also ran a lot faster.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

ProjectPro

JUNE 6, 2025

How would you create a Data Model using SQL commands? Consolidate and develop hybrid architectures in the cloud and on-premises, combining conventional, NoSQL, and Big Data. How do you model a set of entities in a NoSQL database using an optimal technique? What is the difference between Amazon DynamoDB and other NoSQL databases?

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

ProjectPro

JUNE 6, 2025

The data modeler builds, implements, and analyzes data architecture and data modeling solutions using relational, dimensional, and NoSQL databases. SQL Proficiency It is essential to be proficient in SQL, also known as "structured query language," if you want to work as a data modeler. What does a Data Modeler do?

NoSQL 40

NoSQL ETL Tools Certification SQL 40

ProjectPro

JUNE 6, 2025

Spark SQL, for instance, enables structured data processing with SQL. Hive uses HQL, while Spark uses SQL as the language for querying the data. However, no such option is present in Spark SQL. Hive offers the feature for redundant storage while no such feature is present in Spark SQL.

Hadoop 45

Hadoop Java Big Data Tools SQL 45

KDnuggets

OCTOBER 4, 2022

Among the four big NoSQL database types, key-value stores are probably the most popular ones due to their simplicity and fast performance. Let’s further explore how key-value stores work and what are their practical uses.

Database 159

Database NoSQL SQL 159

ProjectPro

JUNE 6, 2025

List of the Best Data Warehouse Tools Amazon Redshift Google BigQuery Snowflake Microsoft Azure Synapse Analytics (Azure SQL Data Warehouse) Teradata Amazon DynamoDB PostgreSQL Hone Your Data Warehousing Skills with ProjectPro's Hands-On Expertise FAQs on Data Warehousing Tools What are Data Warehousing Tools?

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

ProjectPro

JUNE 6, 2025

From working with raw data in various formats to the complex processes of transforming and loading data into a central repository and conducting in-depth data analysis using SQL and advanced techniques, you will explore a wide range of real-world databases and tools. Ratings/Reviews This course has an overall rating of 4.7

Data Engineering 45

Data Engineering Data Engineer Cloud Engineering 45

ProjectPro

JUNE 6, 2025

It provides powerful query capabilities for running SQL queries to access and analyze data. 2) Geospatial Analysis Users can analyze and display geographic data with BigQuery thanks to its usage of geography data types and Google Standard SQL geography functions.

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

ProjectPro

JUNE 6, 2025

In this book, you will study technologies such as Hadoop, Storm , and NoSQL databases, in addition to a general framework for handling big data. It introduces the Lambda Architecture, a scalable, simple-to-implement method that can be built and managed by a small team.

Data Engineering 45

Data Engineering Data Engineer Engineering Lambda Architecture 45

Data Engineering Podcast

JANUARY 21, 2024

For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

ProjectPro

JUNE 6, 2025

Azure Tables: NoSQL storage for storing structured data without a schema. The Data Lake Store, the Analytics Service, and the U-SQL programming language are the three key components of Azure Data Lake Analytics. The query language U-SQL was developed especially for big data analytics. Workload Classification. Workload Isolation.

Data Lake 40

Data Lake Amazon Web Services Data Warehouse Big Data 40

ProjectPro

JUNE 6, 2025

They include relational databases like Amazon RDS for MySQL, PostgreSQL, and Oracle and NoSQL databases like Amazon DynamoDB. Database Variety: AWS provides multiple database options such as Aurora (relational), DynamoDB (NoSQL), and ElastiCache (in-memory), letting startups choose the best-fit tech for their needs.

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

Azure Databricks is closely linked to Azure's computation and storage resources, including Azure Blob Storage, Data Lake Store, SQL Data Warehouse, and HDInsights. Microsoft Azure SQL Database Azure SQL Database, a member of the Azure SQL family, is a relational database service that is continually updated and fully managed for the cloud.

Data Engineering 40

Data Engineering Data Engineer PostgreSQL Engineering 40

ProjectPro

JUNE 6, 2025

Ability to write, analyze, and debug SQL queries Solid understanding of ETL (Extract, Transfer, Load) tools, NoSQL, Apache Spark System, and relational DBMS. Data Architect - Key Skills Solid understanding of programming languages like Java, Python, R, or SQL. Deep expertise in technologies like Python, Java, SQL, Scala, or C++.

Data Science 56

Data Science Data Mining Data Architect BI 56

ProjectPro

JUNE 6, 2025

Azure Cosmos DB Pricing Azure Cosmos DB Tutorial: Getting Started with NoSQL Database Real-World Applications of Azure Cosmos DB Boosting Performance in Cosmos DB: Top Tips and Techniques Azure Cosmos DB Project Ideas Enhance Your Data Management Skills with ProjectPro's Guided Azure Projects! What is Cosmos DB Used for?

Database 40

Database Management MongoDB NoSQL 40

KDnuggets

SEPTEMBER 8, 2023

Also learn the fundamentals of relational databases, NoSQL database categories, and more. Understand the relevance of databases in data science.

Database 135

Database Data Science NoSQL Relational Database 135

ProjectPro

JUNE 6, 2025

Data Language: SQL is the most popular data language. You can expect interview questions from various technologies and fields, such as Statistics, Python, SQL, A/B Testing, Machine Learning , Big Data, NoSQL , etc. Why do you think NoSQL databases can be better than SQL databases?

Recruitment 73

Recruitment Data Science NoSQL Machine Learning 73

ProjectPro

JUNE 6, 2025

There are several ways of interacting with such databases and most of them are based on Structured Query Language (SQL). The other types of databases include key-value, columnar, time-series, NoSQL , etc. To handle NoSQL databases (that do not contain data in rows and columns), data engineers usually use Elasticsearch.

Python 40

Python Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Questions span data warehousing , ETL processes, big data technologies , SQL, data processing, optimization, security, privacy, and data visualization. The on-site assessments cover SQL , analytics, machine learning , and algorithms. How would you optimize a SQL query for a large dataset in a data warehouse?

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

Data Engineering Podcast

FEBRUARY 11, 2018

Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? How is Timescale implemented and how has the internal architecture evolved since you first started working on it? What impact has the 10.0 What impact has the 10.0

PostgreSQL 100

PostgreSQL NoSQL Google Cloud MongoDB 100

ProjectPro

JUNE 6, 2025

Additionally, expertise in specific Big Data technologies like Hadoop, Spark, or NoSQL databases can command higher pay. NoSQL Databases: Familiarize yourself with NoSQL databases like Apache Cassandra, HBase, or MongoDB designed to handle large volumes of unstructured data efficiently.

Big Data 40

Big Data Hadoop Scala NoSQL 40

Rockset

MAY 17, 2022

Limitations of NoSQL SQL supports complex queries because it is a very expressive, mature language. Complex SQL queries have long been commonplace in business intelligence (BI). Hive implemented an SQL layer on Hadoop’s native MapReduce programming paradigm. As a result, the use cases remained firmly in batch mode.

SQL 52

SQL NoSQL Hadoop MongoDB 52

ProjectPro

JUNE 6, 2025

A data engineer is expected to be adept at using ETL (Extract, Transform and Load) tools and be able to work with both SQL and NoSQL databases. Knowledge of SQL queries to manipulate data is also essential for an AI engineer. Finally, you should learn to work with large databases.

Engineering 75

Engineering Software Engineer Software Engineering Deep Learning 75

ProjectPro

JUNE 6, 2025

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. NoSQL, for example, may not be appropriate for message queues. When is it appropriate to use a NoSQL database? When working with large amounts of data, NoSQL databases are an excellent choice.

Big Data 40

Big Data Hadoop Relational Database AWS 40

Data Engineering Podcast

JUNE 10, 2018

To address these shortcomings the engineers at Cockroach Labs have built a globally distributed SQL database with full ACID semantics in Cockroach DB. I know that your SQL syntax is PostGreSQL compatible, so is it possible to use existing ORMs unmodified with CockroachDB?

PostgreSQL 100

PostgreSQL NoSQL Relational Database SQL 100

ProjectPro

JUNE 6, 2025

Additional libraries on top of Spark Core enable a variety of SQL, streaming, and machine learning applications. Spark can integrate with Apache Cassandra to process data stored in this NoSQL database. Spark can connect to relational databases using JDBC, allowing it to perform operations on SQL databases.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

You must have good knowledge of the SQL and NoSQL database systems. SQL is the most popular database language used in a majority of organizations. NoSQL databases are also gaining popularity owing to the additional capabilities offered by such databases. You should also look to master at least one programming language.

Big Data 40

Big Data Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Classification Projects on Machine Learning for Beginners Recommender System Machine Learning Project for Beginners Build a Music Recommendation Algorithm using KKBox's Dataset Build a Text Classification Model with Attention Mechanism NLP Database technologies (SQL, NoSQL, etc.) such as Python/R, Hadoop, AWS, Azure, SQL/NoSQL , etc.

Data Engineering 40

Data Engineering Data Engineer Recruitment Engineering 40