Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Kafka or Kinesis ? Stream processing or an OLAP database? What Is Streaming Data?

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Kafka AWS Amazon Web Services Programming Language 52

Confluent

MAY 23, 2019

Let us cut to the chase: Kafka Summit London session videos are available! This year’s London event was almost double the size of last year, so I’m especially happy to see these numbers on the page: 2 days of Apache Kafka ®. World-class Kafka keynotes. And if you weren’t there? Well, dig in and start learning! 3 keynotes.

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Kafka Cloud Database Engineering 109

Scott Logic

NOVEMBER 6, 2023

In this post we’ll take a whistle-stop tour around the topic of data, going from sources and types through to use cases and the technologies involved in processing data. Often this must be traded off against accuracy or require multiple piplines – see literature around streaming watermarks and the Lambda and Kappa architectures.

Data Lake 52

Data Lake Kafka BI Unstructured Data 52

Pinterest Engineering

SEPTEMBER 29, 2023

Sanchay Javeria | Software Engineer, Ads Data Infrastructure To support metrics reporting for ads from external advertisers and real-time ad budget calculations at Pinterest, we run streaming pipelines using Apache Flink. The first piece of the puzzle was to separate the symptoms from the cause.

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Utilities Coding Kafka Engineering 94

Knowledge Hut

JANUARY 16, 2024

The avenues to acquire the essential skills for a career in ML are plentiful, ranging from Machine Learning online courses and certifications to formal degree programs. Machine learning drives advancements in image and speech recognition, Natural Language Processing (NLP), recommendation systems, and applications like fraud detection.

Machine Learning 98

Machine Learning Engineering Programming Language Algorithm 98

ProjectPro

DECEMBER 28, 2021

Managing, processing, and streamlining large datasets in real-time is a key functionality of big data analytics in an enterprise to enhance decision-making. Table of Contents What is Spark streaming? Kafka Stream vs. Spark Streaming What is Spark streaming? billion by 2030.

Architecture 52

Architecture Kafka Java Scala 52

Rockset

JULY 28, 2022

There are other options: You can bifurcate data coming in, splitting the data into multiple streams that can be sent to multiple data sources. So, this means we generally want to allow our application to talk directly to a database. These services would still need to talk directly to the database.

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Data Engineering Podcast

JANUARY 13, 2019

New products have been launched, more businesses have moved to streaming analytics, and the team at Timescale has been keeping busy. In this episode the TimescaleDB CEO Ajay Kulkarni and CTO Michael Freedman stop by to talk about their 1.0 Can you refresh our memory about what TimescaleDB is?

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Database PostgreSQL SQL MongoDB 100

Towards Data Science

APRIL 3, 2023

Building a Mental Model for Engineers and Anyone in Between Stream Processing can be handled gently and with care, or wildly, and almost out of control! By processing a smaller set of data, more often , you effectively divide and conquer a data problem that may otherwise be cost and time prohibitive.

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Process Data Lake Systems Bytes 84

Rockset

AUGUST 11, 2022

I had the pleasure of recently hosting a data engineering expert discussion on a topic that I know many of you are wrestling with – when to deploy batch or streaming data in your organization’s data stack. On the most-common mistake that data engineers make with streaming data. It’s like learning a different language.

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Bytes Consulting Kafka MongoDB 52

Confluent

MAY 9, 2019

Storing events in a stream and connecting streams via stream processors provide a generic, data-centric, distributed application runtime that you can use to build ETL, event streaming applications, applications for recording metrics and anything else that has a real-time data requirement. Four pillars of event streaming.

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Kafka Pipeline-centric Architecture Database-centric 91

Rockset

APRIL 15, 2022

Out-of-order data are time-stamped events that for a number of reasons arrive after the initial data stream has been ingested by the receiving database or data warehouse. Ever since there has been streaming data, there has been out-of-order data. So why are their analytics still crawling through in batches instead of real time?

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Rockset

NOVEMBER 9, 2021

CDC with Update Timestamps and Kafka One of the simplest ways to implement a CDC solution in both MySQL and Postgres is by using update timestamps. We can then either build bespoke solutions to poll the database for any new records and write them to a target system or a CSV file to be processed later.

MySQL 52

MySQL Kafka AWS Database 52

Netflix Tech

OCTOBER 28, 2021

Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. In this post, Pallavi talks about her journey to Netflix and the challenges that keep the work interesting. Data Engineers of Netflix?—?Interview

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Data Engineering Data Engineer Engineering Software Engineer 69

Pinterest Engineering

MAY 2, 2023

At Pinterest, most of our streaming jobs are built on top of Apache Flink , because Flink is a mature streaming framework with a lot of adoption in the industry. However, when we process a new event for a user, we do not want to read the existing N events, update them, and then write them all back to the respective dataset.

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Lambda Architecture Datasets Software Engineer Software Engineering 66

Data Engineering Weekly

JANUARY 29, 2023

link] Part 1: [link] LucianoSphere: Build custom-informed GPT-3-based chatbots for your website with very simple code ChatGPT is the talk of the town; I found this article an exciting one to build custom GPT-3-based chatbots. Upsolver SQLake lets you process fast-moving data by simply writing a SQL query.

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 52

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. We need something that does not only store data but processes events as they happen. Cloud is one of the key drivers for innovation. Journey from mainframe to cloud.

Cloud 86

Cloud Banking Kafka NoSQL 86

Data Engineering Weekly

JANUARY 8, 2023

Editor’s Note: State Of Data 2023 Conference - 18-Jan-2023 The team Seattle Data Guy is running an excellent day-track online conference, “ The State of Data 2023 ” I’m giving a talk on “The Functional Data Engineering - A Blueprint.” Streaming plus batch unified in a single platform.

Data Engineering 40

Data Engineering Data Engineer Engineering Pipeline-centric 40

Rockset

DECEMBER 9, 2021

Remember when you shopped online and it took a week for your packages to arrive -- and you were fine with it? Online shoppers like relevant product recommendations, but they love when they are offered discounts and bundles for them. Massive , often bursty data streams. Change data capture (CDC) streams.

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Transportation BI SQL Data Warehouse 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Using database tools, they create a robust architecture and later implement the process to develop the database from zero. What is Data Science?

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Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

SEPTEMBER 12, 2023

Founded in late 2019, the livestream shopping platform Whatnot has grown to become one of the largest online marketplaces for collectibles in the U.S. Whatnot brings together commerce and entertainment in categories like trading cards, sports cards, and fashion, to video games, streetwear, and beyond. Think Twitch meets eBay. Let’s dive in.

Machine Learning 52

Machine Learning Data Entertainment SQL 52

Rockset

DECEMBER 9, 2019

The raw data is consistently added to the staging area and then picked up and processed by downstream processes. It continuously ingests raw data from multiple sources--data lakes, data streams, databases--into its storage layer and allows fast SQL access from both visualisation tools and analytic applications.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

AltexSoft

MARCH 30, 2023

The lakehouse platform was founded by the creators of Apache Spark , a processing engine for big data workloads. Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Delta Lake integrations.

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Scala Data Lake BI Google Cloud 64

Databand.ai

DECEMBER 13, 2022

Notably, Charles combines his data engineering experience with a background in business and entrepreneurship, having previously worked as a business and data analyst and earning a Master of Liberal Arts Degree in Psychology from Harvard Extension School and a Certificate in Entrepreneurship Essentials from Harvard Business School Online.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Rockset

DECEMBER 19, 2023

In his expert opinion, he further delineates a recommender system into an 8-step process, as follows: 8-steps Recommendation Process The retrieval or candidate generation stage is expanded into two steps: Retrieval and Filtering. The focus is on recall — ensuring that the pool includes a broad range of potentially relevant items.

Systems 52

Systems Machine Learning Deep Learning Media 52

Pinterest Engineering

AUGUST 18, 2022

Ankita Girish Wagh | Senior Software Engineer, Storage and Caching Introduction and Motivation At Pinterest, HBase is one of the most critical storage backends, powering many online storage services like Zen (graph database), UMS (wide column datastore), and Ixia (near real time secondary indexing service). Do a validation of both data sets.

Data Ingestion 52

Data Ingestion Hadoop Database Kafka 52

Rockset

SEPTEMBER 13, 2022

This functionality is typically implemented by databases that specialize in online transactional processing (OLTP) workflows that emphasize many concurrent operations against a small number of rows. Many times, we try to handle both patterns with the same database and deal with the inconsistent performance as our application scales.

SQL 52

SQL Database Relational Database AWS 52

LinkedIn Engineering

DECEMBER 8, 2022

In this post, we will talk about Hosted Search, our new search solution that allows product developers to integrate search functionality with minimal onboarding and no maintenance or operational overhead, allowing them to instead focus on their products and what they care about most: creating value for our members.

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Pipeline-centric Management Cloud Transportation 55

Rockset

JULY 25, 2019

The main characteristic that distinguishes operational analytics from other types of analytics is that it is “analytics on the fly," which means that signals emanating from the various parts of a business are processed in real-time to feed back into instant decision making for the business. This is another form of operational analytics.

Software Engineer 40

Software Engineer Software Engineering Engineering PostgreSQL 40

Confluent

APRIL 2, 2019

Includes free forever Confluent Platform on a single Apache Kafka ® broker, improved Control Center functionality at scale and hybrid cloud streaming. the event streaming platform built by the original creators of Apache Kafka. Confluent Platform now available “free forever” on a single Kafka broker.

Kafka 21

Kafka Java Cloud Metadata 21

Confluent

AUGUST 19, 2019

This post specifically outlines the process by which we verify partner integrations, and is a means of letting the world know about our partner’s contributions to our connector ecosystem. It points to best practices for anyone writing Kafka Connect connectors. Over the years, we’ve since seen wide adoption of Kafka Connect.

Programming 15

Programming Kafka Database-centric MongoDB 15

Confluent

SEPTEMBER 12, 2019

When Apache Kafka ® consumer group rebalancing clicks, you feel good. This is one of those intellectual influences that sometimes passes beyond notice, but it’s something that’s definitely happening with event streaming. For me, and I think for you, technology is cool by itself. I love being able to witness this kind of transition.

Kafka 9

Kafka ETL System Architecture Retail 9

ProjectPro

NOVEMBER 7, 2016

We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing. These frameworks achieve this feat through distributed processing of the datasets across clusters of computers. The answer is that these tech giants use frameworks like Apache Hadoop.

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Hadoop Architecture IT Big Data 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Walmart observed a significant 10% to 15% increase in online sales for $1 billion in incremental revenue.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

APRIL 4, 2015

” Image Credit: mapr.com During March 2014, there were approximately 17,000 Hadoop Developer jobs advertised online. With the help of our best in class Hadoop faculty, we have gathered top Hadoop developer interview questions that will help you get through your next Hadoop job interview.

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