Monte Carlo

JANUARY 5, 2024

Snowflake announced Snowpipe for streaming and refactored their Kafka connector, and Google announced Pub/Sub could now be streamed directly into the BigQuery. Increasingly, data warehouses and data lakes are moving toward each other in a general shift toward data lakehouse architecture.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Snowflake announced Snowpipe for streaming and refactored their Kafka connector, and Google announced Pub/Sub could now be streamed directly into the BigQuery. Increasingly, data warehouses and data lakes are moving toward each other in a general shift toward data lakehouse architecture.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Podcast

MAY 27, 2018

What are some of the potential pitfalls for automatic schema management in the target database? What are some of the potential pitfalls for automatic schema management in the target database? What are some of the complexities introduced by processing data from multiple customers with various compliance requirements?

Data Pipeline 100

Data Pipeline MongoDB Scala Google Cloud 100

Knowledge Hut

NOVEMBER 28, 2023

Cloud Data engineering is all about designing, programming, and testing software, which is required for modern database solutions. Kafka Kafka is one of the most desired open-source messaging and streaming systems that allows you to publish, distribute, and consume data streams.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Data Engineering Podcast

NOVEMBER 18, 2018

How does Flink compare to other streaming engines such as Spark, Kafka, Pulsar, and Storm? How does Flink compare to other streaming engines such as Spark, Kafka, Pulsar, and Storm? Can you start by describing what Flink is and how the project got started? What are some of the primary ways that Flink is used? How is Flink architected?

Process 100

Process Scala Google Cloud Kafka 100

Rockset

AUGUST 21, 2019

Rockset continuously ingests data streams from Kafka, without the need for a fixed schema, and serves fast SQL queries on that data. We created the Kafka Connect Plugin for Rockset to export data from Kafka and send it to a collection of documents in Rockset. Implementing a working plugin What is Kafka Connect and Confluent Hub?

Kafka 40

Kafka IT Data Storage Relational Database 40

Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute.

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloud Academy

JANUARY 27, 2022

Many of them are already familiar with SQL or have experience working with databases, whether they’re relational or non-relational. Knowing SQL means you are familiar with the different relational databases available, their functions, and the syntax they use.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Knowledge Hut

JUNE 23, 2023

Let us look at the steps to becoming a data engineer: Step 1 - Skills for Data Engineer to be Mastered for Project Management Learn the fundamentals of coding skills, database design, and cloud computing to start your career in data engineering. Coding helps you link your database and work with all programming languages.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Silectis

JANUARY 3, 2021

Cassandra A database built by the Apache Foundation. Database A collection of structured data. Flat File A type of database that stores data in a plain text format. Kafka Apache Kafka is the Apache Foundation’s open-source software platform for streaming. Big Query Google’s cloud data warehouse.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. To comprehend the database and the underlying architecture, you ought to grasp SQL.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 Druid 0.22.0 – Apache Druid is claimed to be a high-performance analytical database competing with ClickHouse. And of course, PostgreSQL is one of the most popular databases. rc0 to the release of 3.0.0.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 Druid 0.22.0 – Apache Druid is claimed to be a high-performance analytical database competing with ClickHouse. And of course, PostgreSQL is one of the most popular databases. rc0 to the release of 3.0.0.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Knowledge Hut

SEPTEMBER 6, 2023

Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing. Database Management : knowing how to work with databases - both relational(like Postgres) and non-relational - is important for efficient storing and retrieval of data.

Big Data 52

Big Data Certification Hadoop Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

Relational databases, nonrelational databases, data streams, and file stores are examples of data systems. Popular Big Data tools and technologies that a data engineer has to be familiar with include Hadoop, MongoDB, and Kafka. One of the most popular ways to store data is in databases, both relational and non-relational.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Grouparoo

OCTOBER 6, 2021

42 Learn to Use a NoSQL Database, but Not like an RDBMS Write answers to questions in NoSQL databases for fast access 43 Let the Robots Enforce the Rules Work with people to standardize and use code to enforce rules 44 Listen to Your Users—but Not Too Much Create a data team vision and strategy. Increase visibility.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

ProjectPro

DECEMBER 7, 2021

Consequently, data stored in various databases lead to data silos -- big data at rest. After that, the data is loaded into the target system, such as a database, data warehouse, or data lake, for analysis or other tasks. You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

AUGUST 29, 2023

These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Common structured data sources include SQL databases like MySQL, Oracle, and Microsoft SQL Server. Apache Kafka and AWS Kinesis are popular tools for handling real-time data ingestion.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Rockset

OCTOBER 20, 2021

Until now, the majority of the world’s data transformations have been performed on top of data warehouses, query engines, and other databases which are optimized for storing lots of data and querying them for analytics occasionally. For instance, let’s say you have streaming data coming in from Kafka or Kinesis. PostgreSQL or MySQL).

SQL 52

SQL PostgreSQL MongoDB NoSQL 52

Knowledge Hut

JULY 24, 2023

Recently, the advent of stream processing has unlocked the door for a new era in database technology. In today’s data-driven world, the future of SQL is entwined with the future of databases and becoming highly significant. According to recent studies, the global database market will grow from USD 63.4

Database 52

Database SQL Process NoSQL 52

Rockset

MARCH 27, 2023

In this post, we’ll explore the differences between real-time analytics databases and stream processing frameworks. Differing Paradigms Stream processing systems and real-time analytics (RTA) databases are both exploding in popularity. Let’s start with a quick summary of both stream processing and RTA databases.

Database 52

Database Process Scala SQL 52

ProjectPro

FEBRUARY 21, 2023

By mastering the fundamentals, you can advance professionally and pursue other technical opportunities with Azure, such as Associate Azure Data Engineer , Associate Azure Database Administrator, etc. You can practice developing Spark applications that integrate with CDP components like Hive and Kafka through hands-on practice.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

LinkedIn Engineering

JANUARY 16, 2024

At the heart of this system was a reliance on a relational database, Oracle, which served as the repository for all member restrictions data. Figure 2: Relational database schema We adopted a pragmatic and scalable approach by distributing member restrictions across different Oracle tables.

Kafka 84

Kafka Relational Database Java Architecture 84

Rockset

APRIL 29, 2019

However, as an operational database optimized for transaction processing, DynamoDB is not well-suited to delivering real-time analytics. DynamoDB has been one of the most popular NoSQL databases in the cloud since its introduction in 2012. It is central to many modern applications in ad tech, gaming, IoT, and financial services.

NoSQL 52

NoSQL PostgreSQL AWS SQL 52

ProjectPro

OCTOBER 15, 2014

Does not have a dedicated metadata database. Directly leverages SQL and is easy to learn for database experts. Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. Operates on the server side of a cluster. Pig supports Avro file format.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Precisely

JANUARY 25, 2024

It frequently also means moving operational data from native mainframe databases to modern relational databases. Mainframe Migration Mainframe migration is a far more comprehensive approach involving the replacement of most or all mainframe applications and databases with cloud-native alternatives.

Metadata 69

Metadata Data Governance Relational Database Government 69

Confluent

SEPTEMBER 19, 2019

When people ask me the very top-level question “why do people use Kafka,” I usually lead with the story in my last post , where I talked about how Apache Kafka ® is helping us deliver on the promises the cloud made to us a decade ago. Industry heavyweights like Capital One use event streaming on Kafka for this very task.

Kafka 14

Kafka Data Pipeline Bytes Data Architect 14

Confluent

JUNE 18, 2019

As the databases professor at my university used to say, it depends. Using SQL to run your search might be enough for your use case, but as your project requirements grow and more advanced features are needed—for example, enabling synonyms, multilingual search, or even machine learning—your relational database might not be enough.

Architecture 95

Architecture Building Kafka Database-centric 95

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are skilled professionals who lay the foundation of databases and architecture. Using database tools, they create a robust architecture and later implement the process to develop the database from zero. Data engineers who focus on databases work with data warehouses and develop different table schemas.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Confluent

FEBRUARY 12, 2019

One of the most common integrations that people want to do with Apache Kafka ® is getting data in from a database. That is because relational databases are a rich source of events. The existing data in a database, and any changes to that data, can be streamed into a Kafka topic. What we’ll cover.

Kafka 87

Kafka MySQL Bytes Java 87

Rockset

OCTOBER 11, 2022

Rockset, on the other hand, is a cloud-native database, removing a lot of the tooling and overhead required to get data into the system. Logstash offers a JDBC input plugin that polls a relational database, like PostgreSQL or MySQL, for inserts and updates periodically.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

ProjectPro

NOVEMBER 14, 2015

This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. Data migration from legacy systems to the cloud is a major use case in organizations that have been into relational databases.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Rockset

MARCH 26, 2023

Breaking Bad… Data Silos We haven’t quite figured out how to avoid using relational databases. Folks have definitely tried, and while Apache Kafka® has become the standard for event-driven architectures, it still struggles to replace your everyday PostgreSQL database instance in the modern application stack.

Cloud 52

Cloud PostgreSQL Kafka Database 52

Edureka

FEBRUARY 9, 2023

This language is used to interact with databases and perform data manipulations and querying. It offers an interactive and user-friendly interface for creating dashboards, reports, and charts from a variety of data sources such as spreadsheets, databases, and cloud-based sources. SQL is also an essential skill for Azure Data Engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

LinkedIn Engineering

MAY 11, 2023

For MaaS, the starting point was co-hosting the web service, relational database ( Postgres ), and Redis -based caching layer on a server. In the extant deployment model, multiple API workers functioned in tandem without sharing common memory or database connectors. We decided to leverage Kafka as a distributed messaging queue.

Management 101

Management PostgreSQL MySQL Kafka 101

Cloudera

MARCH 23, 2023

An MV is a special type of sink that allows us to output data from our query into a tabular format persisted in a PostgreSQL database. Primary key Every MV requires a primary key, as this will be our primary key in the underlying relational database as well. Why use a materialized view? It is set to five minutes by default.

SQL 77

SQL Kafka PostgreSQL Database 77