Data Engineering Podcast

AUGUST 21, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Just connect it to your database/data warehouse/data lakehouse/whatever you’re using and let them do the rest.

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Confluent

JULY 29, 2020

Change Data Capture (CDC) is an excellent way to introduce streaming analytics into your existing database, and using Debezium enables you to send your change data through Apache Kafka®. Although […].

Kafka 104

Kafka Database MongoDB Data 104

Confluent

JULY 17, 2019

Together, MongoDB and Apache Kafka ® make up the heart of many modern data architectures today. Integrating Kafka with external systems like MongoDB is best done though the use of Kafka Connect. The official MongoDB Connector for Apache Kafka is developed and supported by MongoDB engineers.

MongoDB 21

MongoDB Kafka Medical Database 21

Data Engineering Podcast

SEPTEMBER 11, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Email hosts@dataengineeringpodcast.com ) with your story. Email hosts@dataengineeringpodcast.com ) with your story.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Data Engineering Podcast

DECEMBER 4, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. No more shipping and praying, you can now know exactly what will change in your database!

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Striim

AUGUST 26, 2023

Users often have to grapple with intricate, low-level Kafka elements like topics, brokers, partitions, taking focus away from more strategic tasks. AWS MSK : An Apache Kafka-compatible managed streaming platform that also allows users to access other AWS services directly. Frequently Asked Questions What is Apache Kafka?

MongoDB 52

MongoDB Google Cloud Kafka AWS 52

Rockset

JUNE 2, 2020

MongoDB World is going all virtual with MongoDB.live. If you’re short on time, fear not- here are our top 10 MongoDB sessions to watch out for: 10 Join the Data Movement: MongoDB and Apache Kafka One of the go-to picks for companies that need a streaming platform is Apache Kafka. Are REST APIs are your jam?

MongoDB 52

MongoDB Data Lake Kafka NoSQL 52

Data Engineering Podcast

AUGUST 28, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Just connect it to your database/data warehouse/data lakehouse/whatever you’re using and let them do the rest.

Building 100

Building MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 10, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. No more shipping and praying, you can now know exactly what will change in your database!

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

SEPTEMBER 25, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs.

Food 100

Food MongoDB Scala MySQL 100

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

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. These fundamentals will give you a solid foundation in data and datasets.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. Rockset is a real-time analytics database in the cloud that uses an indexing approach to deliver low-latency analytics at scale.

SQL 52

SQL Kafka MongoDB MySQL 52

Data Engineering Podcast

FEBRUARY 11, 2018

The landscape of time series databases is extensive and oftentimes difficult to navigate. Which came first, Timescale the business or Timescale the database, and what is your strategy for ensuring that the open source project and the company around it both maintain their health?

PostgreSQL 100

PostgreSQL NoSQL Google Cloud MongoDB 100

Rockset

NOVEMBER 9, 2021

There are multiple change data capture methods available when using a MySQL or Postgres database. Some of these methods overlap and are very similar regardless of which database technology you are using, others are different. Kafka Connect also has connectors to target systems that can then write these records for you.

MySQL 52

MySQL Kafka AWS Database 52

Knowledge Hut

APRIL 25, 2023

Data engineering is a field that requires a range of technical skills, including database management, data modeling, and programming. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

DECEMBER 26, 2023

They also have an understanding of Database Management Systems, Online Analytical Processing (OLAP), and ETL frameworks as they are responsible for building OLAP using relational and multidimensional databases. Data Architects design, create and maintain database systems according to the business model requirements.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Rockset

OCTOBER 13, 2022

Avoid frequent updates Modern databases like DynamoDB and MongoDB offer CDC streams. If you ever see Kafka events or Snowpipe streaming into your warehouse, just mutter son of a batch and walk away. Your stakeholders ask for fresher data. Snowflake is built for batch. Both query latency and cost-per-query are lower.

MongoDB 52

MongoDB BI Kafka Database 52

Knowledge Hut

JUNE 20, 2023

Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. Database-Centric Engineer: The implementation, upkeep, and populating of analytics databases are the responsibilities of a Database-Centric Engineer. Apache Spark, Microsoft Azure, Amazon Web services, etc.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Ascend.io

SEPTEMBER 14, 2023

It's specialized for database querying. Interpreter / Compiler Interpreted Executed by a database engine, interpreting and executing SQL statements. Declarative and straightforward for database tasks. Its ecosystem revolves around database management and querying. Primarily tailored for database tasks.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Knowledge Hut

APRIL 24, 2024

Realtime Communication: Instructors and students can communicate in real time using Firebase Realtime Database. cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, threshold(gray_image, 127, 255, cv2.THRESH_BINARY) THRESH_BINARY) contours, _ = cv2.findContours(thresh, findContours(thresh, cv2.RETR_TREE,

Software Engineer 52

Software Engineer Software Engineering Coding Project 52

Knowledge Hut

OCTOBER 27, 2023

Realtime Communication: Instructors and students can communicate in real time using Firebase Realtime Database. cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, threshold(gray_image, 127, 255, cv2.THRESH_BINARY) THRESH_BINARY) contours, _ = cv2.findContours(thresh, findContours(thresh, cv2.RETR_TREE,

Software Engineer 98

Software Engineer Software Engineering Coding Project 98

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

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

Rockset

AUGUST 11, 2022

Our talk follows an earlier video roundtable hosted by Rockset CEO Venkat Venkataramani, who was joined by a different but equally-respected panel of data engineering experts, including: DynamoDB author Alex DeBrie ; MongoDB director of developer relations Rick Houlihan ; Jeremy Daly , GM of Serverless Cloud.

Bytes 52

Bytes Consulting Kafka MongoDB 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

Rockset

JUNE 7, 2021

Most patterns require the source system to flag that a change has happened to some data, for example by updating a specific column on a table in the database or putting the changed record onto a queue. This could be as simple as applying an update to a record in the target database. The record in the database would now look as follows.

IT 40

IT Kafka Database MongoDB 40

ProjectPro

FEBRUARY 1, 2017

The data architecture is based on open source standards Pentaho and is used for managing, preparing and integrating data that runs through their environments including Cloudera Hadoop Distribution , HP Vertica, Flume and Kafka. Source : [link] Database Ransom Attacks Hit CouchDB and Hadoop Servers. Gigaom.com, January 23, 2017.

Hadoop 52

Hadoop MongoDB Big Data Kafka 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

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. Database Knowledge Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Rockset

MAY 27, 2021

It could be nested JSON coming from MongoDB. It could be Avro coming from Kafka. Today you will find RocksDBs used in Apache Kafka, it's used in Flink, it's used in CockroachDB. You want to be able to do, for example, standard SQL queries, including JOINs, on whatever your data is, wherever it's coming from.

MongoDB 40

MongoDB Kafka Cloud SQL 40

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

Rockset

OCTOBER 1, 2020

The data sources available include: users (MongoDB): Core customer data such as name, age, gender, address. online_orders (MongoDB): Online purchase data including product details and delivery addresses. instore_orders (MongoDB): In-store purchase data again including product details and store location. SELECT users.id

MongoDB 40

MongoDB Kafka Building Data Warehouse 40

ProjectPro

OCTOBER 5, 2018

Microsoft has announced the addition of new connectors which will allow businesses to use SQL server to query other databases like MongoDB, Oracle, and Teradata. enhance the efficiency, Count Komatsu has combined several big data tools that include Spark, Hadoop, Kafka , Kudu, and Impala from Cloudera. September 24, 2018.

Hadoop 40

Hadoop BI Big Data MongoDB 40

Rockset

JUNE 9, 2020

In the course of implementing the Rockset connector to MongoDB , we did a fair amount of research on the MongoDB user experience, both online and through user interviews. Sharding What is MongoDB Sharding and the Best Practices? This was a recurring theme we heard when speaking with MongoDB users.

MongoDB 52

MongoDB NoSQL Database Kafka 52

Rockset

JUNE 16, 2020

MongoDB.live took place last week, and Rockset had the opportunity to participate alongside members of the MongoDB community and share about our work to make MongoDB data accessible via real-time external indexing. We would be responsible for building and maintaining pipelines from these sources to MongoDB.

MongoDB 52

MongoDB Data Lake PostgreSQL Kafka 52

Knowledge Hut

DECEMBER 21, 2023

It involves building and maintaining data pipelines, databases, and data warehouses. The primary process comprises gathering data from multiple sources, storing it in a database to handle vast quantities of information, cleaning it for further use and presenting it in a comprehensible manner. Knowledge of Hadoop, Spark, and Kafka.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52