Confluent

MAY 29, 2019

In part 1 , we discussed an event streaming architecture that we implemented for a customer using Apache Kafka ® , KSQL from Confluent, and Kafka Streams. In part 3, we’ll explore using Gradle to build and deploy KSQL user-defined functions (UDFs) and Kafka Streams microservices. Introduction. KSQL primer.

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Data Engineering Weekly

NOVEMBER 27, 2022

I have a long list of thoughts on this conversation, which might need a blog post on its own. Maybe Slack is 1% of the company implementing data engineering effectively to drive the product feature, but that is the point of implementing data contract and shifting left for an efficient data creation process.

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Netflix Tech

NOVEMBER 14, 2023

In this three-part blog post series, we introduce you to Psyberg , our incremental data processing framework designed to tackle such challenges! We’ll discuss batch data processing, the limitations we faced, and how Psyberg emerged as a solution. Let’s dive in! What is late-arriving data? Some techniques we used were: 1.

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Confluent

APRIL 30, 2019

With the release of Apache Kafka ® 2.1.0, Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. This framework opens the door for various optimization techniques from the existing data stream management system (DSMS) and data stream processing literature.

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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. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

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Big Data Tools

OCTOBER 10, 2022

This time I learned about Brooklin, a LinkedIn service for streaming data in a heterogeneous environment. The official GitHub for the project says that it is characterized by high reliability and throughput, claiming that Brooklin can run hundreds of streaming pipelines simultaneously. You can find more info on the voting process here.

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Big Data Tools

OCTOBER 10, 2022

This time I learned about Brooklin, a LinkedIn service for streaming data in a heterogeneous environment. The official GitHub for the project says that it is characterized by high reliability and throughput, claiming that Brooklin can run hundreds of streaming pipelines simultaneously. You can find more info on the voting process here.

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Data Engineering Weekly

JULY 9, 2023

link] Capital One: Democratizing machine learning It is an exciting blog post + video interview from Capital One focusing on the people and technology aspect of democratizing the machine learning practice across the org. The blog narrates the optimization and cluster architectural changes by ByteDance on top of ClickHouse.

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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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Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. Understand the significance of data engineering in facilitating data-driven decision-making processes. What is Data Engineering?

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Rockset

JANUARY 3, 2023

This blog compiles real-time data predictions from industry leaders so you know what’s coming in 2023. Confluent’s State of Data in Motion Report found that 97% of companies around the world are using streaming data, making it central to the data landscape.

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ProjectPro

DECEMBER 7, 2021

This blog will give you an in-depth knowledge of what is a data pipeline and also explore other aspects such as data pipeline architecture, data pipeline tools, use cases, and so much more. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications.

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Scott Logic

JUNE 6, 2023

Predictions around this are very hard to make, especially taking into account how fast this field is changing, so it will be interesting to revisit this blog in a couple of years to see how things are. Ultimately, it is an error-prone process where experienced heads are often required to help navigate and make good decisions.

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Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

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Rock the JVM

AUGUST 9, 2022

In this post, we’re going to go over an introduction to the main components of ZIO Streams, how to work with them when things go right, and what to do when things go wrong. As a toy example, we’re going to take a brief foray into asynchronous operations, by connecting two streams to the same concurrent data structure.

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ProjectPro

AUGUST 24, 2021

And, out of these professions, this blog will discuss the data engineering job role. This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase.

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Rockset

FEBRUARY 6, 2019

In this blog post, I will describe the Aggregator Leaf Tailer architecture and its advantages for low-latency data processing and analytics. When we started Rockset , we set out to implement a real-time analytics engine that made the developer's job as simple as possible. We chose ALT for Rockset.

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ProjectPro

NOVEMBER 15, 2021

This blog will walk through the most popular and fascinating open source big data projects. It derives its name “Beam” which is from “Batch” + “Stream” from its functionalities for both batch and streaming the parallel processing pipelines for data.

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AltexSoft

NOVEMBER 7, 2022

The tool represents processes in the form of directed acyclic graphs which visualize casual relationships between tasks and the order of their execution. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. What is Apache Airflow? Airflow webserver.

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Rockset

DECEMBER 19, 2023

This blog post distills his decade of experience into a comprehensive read, offering a detailed overview of the complexities and innovations at every stage of building a real-world recommender system. The process of ranking the candidates is further developed into three distinct steps: Feature Extraction, Scoring, and Ranking.

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Zalando Engineering

NOVEMBER 29, 2017

Second in our series about the use of Apache Kafka’s Streams API by Zalando This is the second in a series about the use of Apache Kafka’s Streams API by Zalando, Europe’s leading online fashion platform. See Ranking Websites in Real-time with Apache Kafka’s Streams API for the first post in the series.

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phData: Data Engineering

JANUARY 3, 2022

We’ll work through the different facets of taking your data and extracting business value with the same rigor and process companies apply to product development. If you have hundreds of thousands of users using a variety of products, you need more tooling and processes at your disposal that enables a thoughtful and scalable approach.

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Zalando Engineering

JANUARY 18, 2017

In many computer programs, the whole logic (or a vast part of it) is essentially the step-by-step processing of data. Of course, this includes the situation when we iterate over the data and just execute the processing logic on every piece of it. Akka Streams have grown from the Reactive Streams initiative.

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AltexSoft

MAY 14, 2021

Not only does Big Data apply to the huge volumes of continuously growing data that come in different formats, but it also refers to the range of processes, tools, and approaches used to gain insights from that data. Also, we’ll introduce you to the popular Big Data analytics tools and existing use cases. Key Big Data characteristics.

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ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Go out and speak with the individuals whose processes you aim to transform with data before you even consider analyzing the data.

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Confluent

AUGUST 1, 2019

The Kafka Streams API boasts a number of capabilities that make it well suited for maintaining the global state of a distributed system. At Imperva, we took advantage of Kafka Streams to build shared state microservices that serve as fault-tolerant, highly available single sources of truth about the state of objects in our system.

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Confluent

SEPTEMBER 20, 2019

As a distributed system for collecting, storing, and processing data at scale, Apache Kafka ® comes with its own deployment complexities. To simplify all of this, different providers have emerged to offer Apache Kafka as a managed service. Before Confluent Cloud was announced , a managed service for Apache Kafka did not exist.

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Monte Carlo

JULY 7, 2022

You can read more about Convoy’s approach from our blog with their Head of Product, Data Platform, Chad Sanderson, “ The modern data warehouse is broken.” On the process side, data needed to become a first class citizen during upstream service updates, including proactive downstream communication. Image courtesy of Andrew Jones.

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Confluent

JULY 31, 2019

Delivers the new Confluent Operator for cloud-native automation on Kubernetes, a redesigned Confluent Control Center user interface to simplify how you manage event streams, and a preview of Role-Based Access Control for enterprise-grade security. Automate Kafka operations for production environments.

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Confluent

SEPTEMBER 13, 2019

Static Membership is an enhancement to the current rebalance protocol that aims to reduce the downtime caused by excessive and unnecessary rebalances for general Apache Kafka ® client implementations. This applies to Kafka consumers, Kafka Connect, and Kafka Streams. Take a Kafka consumer, for example.

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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.

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ProjectPro

NOVEMBER 7, 2016

This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing. Understanding the Hadoop architecture now gets easier!

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ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry. that leverage big data analytics and tools.

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Cloudera

JULY 26, 2021

The irreversible shift towards digital-native / digital-first consumption , working and learning paradigms has introduced new remote or hybrid working. The proliferation of real-time processing by deploying event-driven architectures (e.g., hybrid or public, multi-cloud) and advanced analytical frameworks (e.g.,

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Confluent

OCTOBER 24, 2019

I’ve written an event sourcing bank simulation in Clojure (a lisp build for Java virtual machines or JVMs) called open-bank-mark , which you are welcome to read about in my previous blog post explaining the story behind this open source example. Also, there are several functions wrapping the Java clients for Kafka.

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