Lyft Engineering

NOVEMBER 29, 2023

Introduction At Lyft, we have used systems like Apache ClickHouse and Apache Druid for near real-time and sub-second analytics. Sub-second query systems allow for near real-time data explorations and low latency, high throughput queries, which are particularly well-suited for handling time-series data.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Rockset

JULY 28, 2022

CDC enables true real-time analytics on your application data, assuming the platform you send the data to can consume the events in real time. Options For Change Data Capture on MongoDB Apache Kafka The native CDC architecture for capturing change events in MongoDB uses Apache Kafka.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

Rockset

APRIL 26, 2022

As Kafka Summit is in full swing in London this week and the topic of event streaming is all over my Linkedin feed, I saw a post asking " Is streaming dead? That streaming is rocking and with Kafka Summit this week, I thought it a good time to emphasize the importance of streaming data in today’s modern real-time data stack.

Kafka 52

Kafka Data Warehouse Database Data 52

Cloudera

JUNE 7, 2021

It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. . Improved Kafka and Schema Registry integration. Flink SQL catalogs are now supported directly on the streambuilder platform allowing easy access to data stored in other systems.

Kafka 101

Kafka SQL Accessible Accessibility 101

Precisely

FEBRUARY 26, 2024

In decades past, IT systems were relatively self-contained. Today’s systems, however, are highly interconnected and constantly in flux. Naturally, the highly interconnected nature of modern systems opens the door to plenty of new possibilities, but it also creates some new challenges. This has some very real business benefits.

IT 75

IT Banking Programming Language Systems 75

Netflix Tech

AUGUST 30, 2021

In the Device Management Platform, this is achieved by having device updates be event-sourced through the control plane to the cloud so that NTS will always have the most up-to-date information about the devices available for testing. In particular, the Kafka integration is the most relevant for this blog post.

Management 85

Management Kafka Transportation Cloud 85

Cloudera

JULY 18, 2022

We will also use the information produced by the streaming analytics jobs to feed different downstream systems and dashboards. . This information will be efficiently fed to downstream systems through Kafka, so that appropriate actions, like blocking the card or calling the user, can be initiated immediately. Use case recap.

Process 86

Process Kafka Scala SQL 86

Data Engineering Podcast

DECEMBER 24, 2023

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Can you describe your experiences with Kafka? What are the operational challenges that you have had to overcome while working with Kafka?

Kafka 245

Kafka Data Lake High Quality Data SQL 245

Data Engineering Weekly

SEPTEMBER 24, 2023

Request Access to Data Validate with Exploration [link] Ramp: How Ramp Accelerated Machine Learning Development to Simplify Finance Ramp writes about its machine learning infrastructure and the choice of Metaflow for running the ML workload. Those challenges are a thing of the past with RudderStack’s Kafka source integration.

Data Engineering 67

Data Engineering Data Engineer Engineering Kafka 67

Knowledge Hut

JUNE 26, 2023

Top Data Engineering Projects with Source Code Data engineers make unprocessed data accessible and functional for other data professionals. Source Code: Stock and Twitter Data Extraction Using Python, Kafka, and Spark 2. If you are struggling with Data Engineering projects for beginners, then Data Engineer Bootcamp is for you.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Cloudera

AUGUST 10, 2021

Apache Ozone enhancements deliver full High Availability providing customers with enterprise-grade object storage and compatibility with Hadoop Compatible File System and S3 API. . Impala Row Filtering to set access policies for rows when reading from a table. Figure 1: sales group SELECT access.

Cloud 96

Cloud Kafka Metadata SQL 96

Data Engineering Podcast

SEPTEMBER 28, 2020

Summary Kafka has become a de facto standard interface for building decoupled systems and working with streaming data. To make the benefits of the Kafka ecosystem more accessible and reduce the operational burden, Alexander Gallego and his team at Vectorized created the Red Panda engine.

Kafka 100

Kafka BI Big Data Data Engineering 100

Cloudera

MARCH 14, 2023

For example, a developer may be asked to tap into the data of a newly acquired application, parsing and transforming it before delivering it to the business’s favorite analytical system where it can be joined with existing data sets. You want to see how to get data from Kafka and write it to Iceberg?

Data Pipeline 81

Data Pipeline Designing Kafka Metadata 81

Knowledge Hut

APRIL 25, 2024

If you pursue the MSc big data technologies course, you will be able to specialize in topics such as Big Data Analytics, Business Analytics, Machine Learning, Hadoop and Spark technologies, Cloud Systems etc. Spark is a fast and general-purpose cluster computing system. What Are Big Data T echnologies?

Big Data 98

Big Data Technology NoSQL Hadoop 98

Data Engineering Podcast

MAY 11, 2020

His most recent endeavor at StreamNative is focused on combining the capabilities of Pulsar with the cloud native movement to make it easier to build and scale real time messaging systems with built in event processing capabilities. How have projects such as Kafka and Pulsar impacted the broader software and data landscape?

Lambda Architecture 100

Lambda Architecture Cloud Kafka Hadoop 100

Precisely

SEPTEMBER 12, 2023

Precisely data integrity solutions fuel your Confluent and Apache Kafka streaming data pipelines with trusted data that has maximum accuracy, consistency, and context and we’re ready to share more with you at the upcoming Current 2023. Let’s cover some additional information to know before attending.

Kafka 52

Kafka Data Integration Data Pipeline Datasets 52

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. What are some of the notable changes/advancements at Fivetran in the last 3 years?

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 27, 2021

Datastax has recently introduced a new managed offering for Pulsar workloads in the form of Astra Streaming that lowers those barriers and make stremaing workloads accessible to a wider audience. How do you handle migrating existing projects, particularly if they are using Kafka currently?

Building 100

Building Management Kafka Data Warehouse 100

Data Engineering Podcast

MARCH 8, 2021

Summary A majority of the time spent in data engineering is copying data between systems to make the information available for different purposes. This introduces challenges such as keeping information synchronized, managing schema evolution, building transformations to match the expectations of the destination systems.

IT 100

IT Data Warehouse MongoDB Kafka 100

Cloudera

JANUARY 31, 2024

Replication is a crucial capability in distributed systems to address challenges related to fault tolerance, high availability, load balancing, scalability, data locality, network efficiency, and data durability. Introduction Kafka as an event streaming component can be applied to a wide variety of use cases.

Management 68

Management Kafka Big Data Cloud 68

Cloudera

MAY 1, 2023

Cloudera is therefore uniquely able to decouple the development of business/event logic from other aspects of application development, to further empower domain experts and accelerate development of real time data apps. An example of a project might be a fraud detection system implemented in Flink/SSB.

SQL 76

SQL Project Kafka Accessible 76

Data Engineering Weekly

AUGUST 6, 2023

At Data Engineering Weekly, I wrote an article 15 months back narrating how dbt is not a separate model but part of the larger orchestration system. link] Sponsored: Great Data Debate–The State of Data Mesh Since 2019, the data mesh has woven itself into every blog post, event presentation, and webinar.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Cloudera

DECEMBER 9, 2022

This observation further emphasizes the need for universal developer accessibility , which makes sure that developer tooling is easy to use for newcomers while giving power users the advanced options they need. A critical aspect of universal developer accessibility is to provide dataflow development as a self-service offering to developers.

Designing 96

Designing Coding Google Cloud AWS 96

Rockset

MARCH 19, 2020

Intro In recent years, Kafka has become synonymous with “streaming,” and with features like Kafka Streams, KSQL, joins, and integrations into sinks like Elasticsearch and Druid, there are more ways than ever to build a real-time analytics application around streaming data in Kafka.

Kafka 40

Kafka Database Process SQL 40

Rockset

SEPTEMBER 26, 2023

AI-powered applications almost always need access to real-time data to deliver accurate results in a responsive user experience that the market has come to expect. As smart as ChatGPT appears to be, it can’t summarize current events accurately if it was last trained a year ago and not told what’s happening now.

Metadata 64

Metadata Kafka Cloud Database 64

Rockset

APRIL 3, 2020

Such events would also lead to business loss. PROPOSED SOLUTION: The proposal is to build a fleet management system for operators to manage their fleet efficiently. Rockset This SaaS service allows fast SQL on NoSQL data from varied sources like Kafka, DynamoDB, S3 and more. We had selected Amazon MSK to run Kafka and Spark.

Data Pipeline 40

Data Pipeline Systems Management NoSQL 40

Cloudera

APRIL 20, 2021

It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. The primary purpose is to present the most up-to-date operational events for the user to stay on top of the business needs and take action as changes happen in real-time.

Hospitality 92

Hospitality Kafka Retail Data Ingestion 92

LinkedIn Engineering

DECEMBER 19, 2023

The framework incorporates proactive measures to monitor critical events, provides deployment insights, and issues proper notifications to enable seamless deployments. The system maintains a robust deployment history, seamlessly integrating with tools like version drift to detect deployed version differences.

Big Data 92

Big Data Hadoop Metadata Data 92

Towards Data Science

APRIL 3, 2023

From Enormous Data back to Big Data Say you are tasked with building an analytics application that must process around 1 billion events (1,000,000,000) a day. thousand (k) events a second (or around 695k events a minute if the event stream is constant), which is an easier number to rationalize. reference). Listing 9–1.

Process 87

Process Data Lake Systems Bytes 87

Rockset

MARCH 10, 2022

This is the first post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. Earlier at Yahoo, he was one of the founding engineers of the Hadoop Distributed File System. Event streaming/stream processing has been around for almost a decade.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Zalando Engineering

NOVEMBER 29, 2017

See Ranking Websites in Real-time with Apache Kafka’s Streams API for the first post in the series. Running Kafka Streams applications in AWS At Zalando, Europe’s leading online fashion platform, we use Apache Kafka for a wide variety of use cases. Our team at Zalando was an early adopter of the Kafka Streams API.

Kafka 40

Kafka AWS Amazon Web Services Utilities 40

Data Engineering Podcast

OCTOBER 5, 2020

In this episode founders DeVaris Brown and Ali Hamidi explain how their tenure at Heroku informed their approach to making data integration self service, how the platform is architected, and how they have designed their system to adapt to the continued evolution of the data ecosystem.

Data Integration 100

Data Integration Kafka Data Lake Machine Learning 100

Snowflake

AUGUST 16, 2023

Custom Event Billing capabilities enable you to build your own pricing strategy. You can charge customers based on their usage and specify billing events based on your preferences, such as consumed rows, ingested rows and more. The new Kafka connector, built with Snowpipe Streaming , now supports schema detection and evolution.

Scala 52

Scala Transportation Kafka Data Lake 52

Knowledge Hut

MAY 3, 2024

Spark Streaming Vs Kafka Stream Now that we have understood high level what these tools mean, it’s obvious to have curiosity around differences between both the tools. Spark Streaming Kafka Streams 1 Data received from live input data streams is Divided into Micro-batched for processing. 6 Spark streaming is a standalone framework.

Kafka 98

Kafka Scala Java Amazon Web Services 98

Data Engineering Podcast

AUGUST 24, 2020

The key to those solutions is a robust and flexible metadata management system. With their open-source foundation, fixed pricing, and unlimited volume, they are enterprise ready, but accessible to everyone. The key to those solutions is a robust and flexible metadata management system.

Metadata 100

Metadata Management Kafka Data Engineering 100

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Netflix Tech

JUNE 7, 2021

By collecting, accessing and analyzing network data from a variety of sources like VPC Flow Logs , ELB Access Logs, eBPF flow logs on the instances, etc, we can provide network insight to users and central teams through multiple data visualization techniques like Lumen , Atlas , etc.

Transportation 130

Transportation AWS Cloud Metadata 130