Netflix Tech

MARCH 10, 2023

Studio applications use this service to store their media assets, which then goes through an asset cycle of schema validation, versioning, access control, sharing, triggering configured workflows like inspection, proxy generation etc. This pattern grows over time when we need to access and update the existing assets metadata.

Management 94

Management Kafka Metadata Media 94

Afterpay Tech

SEPTEMBER 6, 2022

Photo by Leon S on Unsplash By: Jing Li Summary This article articulates the challenges, innovation and success of the Kafka implementation in Afterpay’s Global Payments Platform in the PCI zone. Context The asynchronous processing capability that Kafka offers opens up numerous innovation opportunities to interact with other services.

Kafka 52

Kafka AWS Metadata Data Warehouse 52

Cloudera

AUGUST 10, 2021

Impala Row Filtering to set access policies for rows when reading from a table. Atlas / Kafka integration provides metadata collection for Kafa producers/consumers so that consumers can manage, govern, and monitor Kafka metadata and metadata lineage in the Atlas UI. Figure 1: sales group SELECT access.

Cloud 97

Cloud Kafka Metadata SQL 97

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

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. In what follows, we provide some context around how a processor topology was generated inside Kafka Streams before 2.1, Kafka Streams topology generation 101.

Kafka 89

Kafka Coding Process Bytes 89

Netflix Tech

JUNE 1, 2023

It also included metadata about ads, such as ad placement and impression-tracking events. We stored these responses in a Keystone stream with outputs for Kafka and Elasticsearch. A Kafka consumer retrieved the playback manifests with ad metadata and simulated a device playing the content and triggering the impression-tracking events.

Algorithm 136

Algorithm Metadata Kafka Systems 136

Rockset

SEPTEMBER 14, 2021

We’re introducing a new Rockset Integration for Apache Kafka that offers native support for Confluent Cloud and Apache Kafka, making it simpler and faster to ingest streaming data for real-time analytics. With the Kafka Integration, users no longer need to build, deploy or operate any infrastructure component on the Kafka side.

Kafka 52

Kafka SQL MongoDB Computer Science 52

LinkedIn Engineering

JUNE 26, 2023

For example, developers can provision Kafka topics, Espresso tables, Venice stores and more via Nuage , our internal cloud-like infra management platform. A developer would need to write and operationalize a custom stream processing job to replicate their Brooklin datastream into a Kafka topic.

Data Pipeline 112

Data Pipeline Kafka MySQL SQL 112

Data Engineering Podcast

NOVEMBER 20, 2022

Summary The majority of blog posts and presentations about data engineering and analytics assume that the consumers of those efforts are internal business users accessing an environment controlled by the business. Atlan is the metadata hub for your data ecosystem. Hevo]([link] Are you sick of repetitive, time-consuming ELT work?

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Podcast

MAY 18, 2021

High-growth startups use Molecula’s feature store because of its unprecedented speed, cost savings, and simplified access to all enterprise data. From feature extraction to model training to production, the Molecula feature store provides continuously updated feature access, reuse, and sharing without the need to pre-process data.

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

Cloudera

OCTOBER 7, 2021

Data and Metadata: Data inputs and data outputs produced based on the application logic. Also included, business and technical metadata, related to both data inputs / data outputs, that enable data discovery and achieving cross-organizational consensus on the definitions of data assets.

Architecture 124

Architecture Metadata Government Kafka 124

Precisely

JULY 21, 2023

Used by more than 75% of the Fortune 500, Apache Kafka has emerged as a powerful open source data streaming platform to meet these challenges. But harnessing and integrating Kafka’s full potential into enterprise environments can be complex. This is where Confluent steps in.

Data Integration 52

Data Integration Kafka Bytes Banking 52

Cloudera

JUNE 16, 2022

In 2015, Cloudera became one of the first vendors to provide enterprise support for Apache Kafka, which marked the genesis of the Cloudera Stream Processing (CSP) offering. Today, CSP is powered by Apache Flink and Kafka and provides a complete, enterprise-grade stream management and stateful processing solution. Who is affected?

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Cloudera

MARCH 2, 2023

It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets.

Process 113

Process SQL Kafka Database 113

Rock the JVM

FEBRUARY 5, 2023

In this article we will see: Why it’s powerful and how it helps democratize Stream Processing and Analytics Understand basic concepts around Streaming and Flink SQL Setup Kafka and Flink Clusters and get started with Flink SQL Understand different kinds of Processing Operators and Functions Different ways of running Flink SQL Queries 1.

SQL 61

SQL Kafka Metadata Database 61

Data Engineering Weekly

MARCH 24, 2024

The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems. The APIs support emitting unstructured log lines and typed metadata key-value pairs (per line). The extracted key-value pairs are written to the line’s metadata.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Cloudera

SEPTEMBER 28, 2020

The customer also wanted to utilize the new features in CDP PvC Base like Apache Ranger for dynamic policies, Apache Atlas for lineage, comprehensive Kafka streaming services and Hive 3 features that are not available in legacy CDH versions. Attribute-based access control and SparkSQL fine-grained access control. Cluster Type.

Cloud 131

Cloud Kafka Professional Services Metadata 131

ProjectPro

JULY 8, 2021

A detailed introduction to Apache Kafka Architecture, one of the most popular messaging systems for distributed applications. Kafka Streams and Kafka Connect were used to keep track of the threat of the COVID-19 virus and analyze the data for a more thorough response on local, state, and federal levels.

Kafka 40

Kafka Architecture IT Big Data 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. Rockset has built an integration that offers native support for Confluent Cloud and Apache Kafka®, making it simple and fast to ingest real-time streaming data for AI applications.

Metadata 64

Metadata Kafka Cloud Database 64

Precisely

JANUARY 25, 2024

To avoid burdening mainframe databases with constant I/O instructions and acknowledgments and prevent latency issues, best practices call for the use of event streaming platforms like Kafka, Amazon Kinesis, Rabbit MQ, or others. This facilitates a continuous streaming approach, allowing for extremely high throughput rates. Best Practice 2.

Metadata 67

Metadata Data Governance Relational Database Government 67

Confluent

AUGUST 29, 2019

We know that Apache Kafka ® is great when you’re dealing with streams, allowing you to conveniently look at streams as tables. In an identity/access management application, it’s the relationships between roles and their privileges that matters most. The approach we’ll use works with any Kafka run though. 8, and so on.

Kafka 55

Kafka Process Algorithm Cloud 55

Picnic Engineering

SEPTEMBER 8, 2022

We use the RabbitMQ Source connector for Apache Kafka Connect. One may wonder why don’t we replace RabbitMQ with Apache Kafka everywhere? In order to answer the first question, we should take a closer look at the difference between RabbitMQ and Apache Kafka in terms of services parallelism.

Kafka 52

Kafka Metadata AWS Java 52

AltexSoft

FEBRUARY 11, 2023

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Metadata management skills Metadata management unlocks the value of a company’s data and it’s a data architect’s task to ensure metadata principles are applicable to all data a business has.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JUNE 29, 2021

Your search for Apache Kafka interview questions ends right here! Let us now dive directly into the Apache Kafka interview questions and answers and help you get started with your Big Data interview preparation! How to study for Kafka interview? What is Kafka used for? What are main APIs of Kafka?

Kafka 40

Kafka Bytes Big Data Java 40

LinkedIn Engineering

JANUARY 16, 2024

When malicious intent is detected, we are swift to respond, employing a range of measures such as imposing challenges to verify authenticity, and in certain cases, restricting a member’s access to the LinkedIn platform. These records held vital metadata linked to the restriction, including essential timestamps.

Kafka 84

Kafka Relational Database Java Architecture 84

Cloudera

MARCH 14, 2023

Creating data flows from scratch Developers access the Flow Designer through the new Flow Design menu item in Cloudera DataFlow (Figure 2), which will show an overview of all existing drafts across workspaces that you have access to. You want to see how to get data from Kafka and write it to Iceberg?

Data Pipeline 83

Data Pipeline Designing Kafka Metadata 83

Rockset

APRIL 18, 2023

Vector search has seen an explosion in popularity due to improvements in accuracy and broadened accessibility to the models used to generate embeddings. Fast Search: Combine vector search and selective metadata filtering to deliver fast, efficient results.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Precisely

MAY 31, 2023

In the same way that big cloud-platform providers offer simplified access to infrastructure, and data cloud providers like Databricks and Snowflake have vastly simplified access to data and analytics, modern data integrity tools must streamline and automate data integrity processes.

Data Integration 52

Data Integration Metadata Data Governance Data 52

Data Engineering Weekly

JULY 9, 2023

ByteDance open sources ByConity, a scalable cloud-native data warehouse built on top of ClickHouse using FoundationDB for its metadata storage. Atlan AI leverages metadata that Atlan captures across the data stack to make AI part of your data stack. link] Grab: Zero traffic cost for Kafka consumers.

Data Engineering 52

Data Engineering Data Engineer Engineering Lambda Architecture 52

Rockset

FEBRUARY 14, 2020

I walk through an end to end integration of requesting data from the car, streaming it into a Kafka Topic and using Rockset to expose the data via its API to create real time visualisations in D3. Getting started with Kafka When starting with any new tool I find it best to look around and see the art of the possible.

Kafka 40

Kafka SQL Metadata Bytes 40

Netflix Tech

SEPTEMBER 29, 2022

Timestone clients can create queues, enqueue messages with user-defined deadlines and metadata, then dequeue these messages in an earliest-deadline-first (EDF) fashion. messages that belong to queue X and have metadata Y”) is also supported. Allow for dequeueing and queue depth querying using filters (metadata key-value pairs) 4.

Systems 85

Systems Metadata Media Kafka 85

Cloudera

FEBRUARY 9, 2021

A new solution integrating cloud object storage, with Cloudera’s NiFi dataflows, a Kafka datahub, and a Hive virtual warehouse in the CDW service allows businesses to take the best advantage of this public cloud trend. In the real-time layer, Kafka automatically cleans the historical events with configurable retention. Cost-Effective.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Data Engineering Podcast

APRIL 13, 2020

Summary The software applications that we build for our businesses are a rich source of data, but accessing and extracting that data is often a slow and error-prone process. What are some of the necessary metadata that should be maintained along with operational metrics?

Data Collection 100

Data Collection Coding Metadata Kafka 100

Cloudera

JULY 15, 2021

All three will be quorums of Zookeepers and HDFS Journal nodes to track changes to HDFS Metadata stored on the Namenodes. Often it is simpler to set up perimeter security when you allow corporate network traffic to only flow to these nodes, as opposed to allowing access to Masters and Workers directly. . Networking .

Architecture 100

Architecture Cloud Kafka Hadoop 100

Cloudera

AUGUST 10, 2021

or higher with Kerberos enabled and admin access to both Ranger and Atlas. For example, my data volume could contain multiple buckets for every stage of the data, and I can control who accesses each stage. I mentioned at the beginning that you’d require a user with fairly open access in Hive and Ozone. Before we begin.

Hadoop 104

Hadoop Kafka Datasets Government 104