Snowflake

APRIL 19, 2023

In Part 2 , we went over ingestion capabilities with Snowflake’s Connector for Kafka using Snowpipe file-based ingestion. There is no intermediary step in cloud storage before data is made available in Snowflake; this reduces architectural complexity and reduces end-to-end latency. What is Snowpipe Streaming?

Data Ingestion 57

Data Ingestion Kafka Java Data Pipeline 57

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. gradlew composeUp. The KSQL pipeline flow.

Kafka 93

Kafka Management Bytes SQL 93

Cloudera

MARCH 31, 2021

One of our customers, Commerzbank, has used the CDP Public Cloud trial to prove that they can combine both Google Cloud and CDP to accelerate their migration to Google Cloud without compromising data security or governance. . Google Cloud Storage buckets – in the same subregion as your subnets .

Google Cloud 92

Google Cloud Cloud Amazon Web Services Cloud Storage 92

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. What are the Different Storage Layers Available in Snowflake? They are flexible, secure, and provide exceptional performance.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Data Engineering Podcast

MAY 27, 2018

Links Alooma Convert Media Data Integration ESB (Enterprise Service Bus) Tibco Mulesoft ETL (Extract, Transform, Load) Informatica Microsoft SSIS OLAP Cube S3 Azure Cloud Storage Snowflake DB Redshift BigQuery Salesforce Hubspot Zendesk Spark The Log: What every software engineer should know about real-time data’s unifying abstraction by Jay (..)

Data Pipeline 100

Data Pipeline MongoDB Scala Google Cloud 100

Big Data Tools

JUNE 8, 2022

And yet it is still compatible with different clouds, storage formats (including Kudu , Ozone , and many others), and storage engines. Kafka: Mark KRaft as Production Ready – One of the most interesting changes to Kafka from recent years is that it now works without ZooKeeper.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Big Data Tools

JUNE 8, 2022

And yet it is still compatible with different clouds, storage formats (including Kudu , Ozone , and many others), and storage engines. Kafka: Mark KRaft as Production Ready – One of the most interesting changes to Kafka from recent years is that it now works without ZooKeeper.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Cloudera

OCTOBER 26, 2020

*For clarity, the scope of the current certification covers CDP-Private Cloud Base. Certification of CDP-Private Cloud Experiences will be considered in the future. The certification process is designed to validate Cloudera products on a variety of Cloud, Storage & Compute Platforms.

Certification 86

Certification Cloud Kafka Unstructured Data 86

Knowledge Hut

JUNE 26, 2023

Stock and Twitter Data Extraction Using Python, Kafka, and Spark Project Overview: The rising and falling of GameStop's stock price and the proliferation of cryptocurrency exchanges have made stocks a topic of widespread attention. Source Code: Stock and Twitter Data Extraction Using Python, Kafka, and Spark 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

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 106

Machine Learning Python Kafka Java 106

Knowledge Hut

OCTOBER 27, 2023

Setting-Up Personal Home Cloud Setting-Up Personal Home Cloud project is an exciting software engineering project that requires a good understanding of hardware and software configurations, cloud storage solutions, and security measures.

Software Engineer 98

Software Engineer Software Engineering Coding Project 98

Knowledge Hut

APRIL 24, 2024

Setting-Up Personal Home Cloud Setting-Up Personal Home Cloud project is an exciting software engineering project that requires a good understanding of hardware and software configurations, cloud storage solutions, and security measures.

Software Engineer 52

Software Engineer Software Engineering Coding Project 52

Cloudera

SEPTEMBER 15, 2020

Cloudera and Microsoft have been working together closely on this integration, which greatly simplifies the security administration of access to ADLS-Gen2 cloud storage. makes all the richness and simplicity of Apache Ranger authorization available for access to ADLS-Gen2 cloud-storage. Cloudera Data Platform 7.2.1

Accessible 77

Accessible Accessibility Cloud Cloud Storage 77

Confluent

OCTOBER 23, 2019

If you’ve worked with the Apache Kafka ® and Confluent ecosystem before, chances are you’ve used a Kafka Connect connector to stream data into Kafka or stream data out of it. This article will cover the basic concepts and architecture of the Kafka Connect framework. What is Kafka Connect?

Kafka 15

Kafka Cloud Storage Cloud Database 15

Monte Carlo

APRIL 24, 2023

Google Cloud Platform and/or BigLake Google offers a couple options for building data lakes. You could use Google Cloud Storage (GCS) to store your data or there’s the new BigLake solution to build a distributed data lake that spans across warehouses, object stores and clouds (even those not on Google’s cloud).

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

AUGUST 21, 2020

One is data at rest, for example in a data lake, warehouse, or cloud storage and from there they can do analytics on this data and that is predominantly around what has already happened or around how to prevent something from happening in the future.

Banking 61

Banking Kafka Cloud Storage Government 61

ProjectPro

AUGUST 24, 2021

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. Cloud composer and PubSub outputs are Apache Beam and connected to Google Dataflow. Collection happens in the Kafka topic.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Zalando Engineering

DECEMBER 18, 2017

Backing up Apache Kafka and Zookeeper to S3 What is Apache Kafka? Apache Kafka is a distributed streaming platform used for building real-time data pipelines and streaming applications. Apache Kafka lowers this risk of data loss with replication across brokers. Kafka Connect will load all jars put in the./kafka-connect/jars

Kafka 40

Kafka AWS Cloud Storage Data 40

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.

Kafka 21

Kafka Management Cloud AWS 21

Knowledge Hut

APRIL 25, 2023

Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale. Apache Kafka Real-time data processing is supported by Apache Kafka , an open-source distributed activity streaming platform. Some of its key features are mentioned here.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Rockset

NOVEMBER 7, 2018

To this end, a CNDB maintains a consistent image of the database--data, indexes, and transaction log--across cloud storage volumes to meet user objectives, and harnesses remote CPU workers to perform critical background work such as compaction and migration. The answer is twofold.

Database 40

Database Cloud Cloud Storage MySQL 40

ProjectPro

DECEMBER 7, 2021

You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines. Source Code: Build a Data Pipeline using Airflow, Kinesis, and AWS Snowflake Apache Kafka The primary feature of Apache Kafka , an open-source distributed event streaming platform, is a message broker (also known as a distributed log).

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Confluent

OCTOBER 16, 2019

Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers. Ingesting the data.

Kafka 19

Kafka Building Data Coding 19

Edureka

FEBRUARY 9, 2023

A data engineer should be familiar with popular Big Data tools and technologies such as Hadoop, MongoDB, and Kafka. Because companies are increasingly replacing physical servers with cloud services, data engineers must understand cloud storage and cloud computing.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

AltexSoft

JULY 29, 2022

Streaming analytics became possible with the introduction of Apache Kafka , Apache Spark , Apache Storm , Apache Flink , and other tools to build real-time data pipelines. Two other most-wanted Big Data instruments — Apache Kafka and Apache Spark — belong to the same ecosystem.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Rockset

MARCH 15, 2021

Using RocksDB’s remote compaction feature, only one replica performs indexing and compaction operations remotely in cloud storage. For each commonly used data source (for example S3, Kafka, MongoDB, DynamoDB, etc.), Because Rockset is a primary-less system, write operations are handled by a distributed log.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Rockset

JUNE 7, 2021

Reference Debezium Architecture To handle the queuing of changes, Debezium uses Kafka. The downside is that to use Debezium you also have to deploy a Kafka cluster so this should be weighed up when assessing your use case.

IT 40

IT Kafka Database MongoDB 40

Knowledge Hut

SEPTEMBER 26, 2023

Key connectivity features include: Data Ingestion: Databricks supports data ingestion from a variety of sources, including data lakes, databases, streaming platforms, and cloud storage. This flexibility allows organizations to ingest data from virtually anywhere.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

AltexSoft

MARCH 30, 2023

Source: Databricks Delta Lake is an open-source, file-based storage layer that adds reliability and functionality to existing data lakes built on Amazon S3, Google Cloud Storage, Azure Data Lake Storage, Alibaba Cloud, HDFS ( Hadoop distributed file system), and others. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake BI Google Cloud 64

ProjectPro

JULY 30, 2021

What are some popular use cases for cloud computing? Cloud storage - Storage over the internet through a web interface turned out to be a boon. With the advent of cloud storage, customers could only pay for the storage they used. BigQuery, Google Cloud Storage) to make more complex systems.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Monte Carlo

AUGUST 19, 2023

Regardless of which side you take, you quite literally cannot build a modern data platform without investing in cloud storage and compute. Snowflake, a cloud data warehouse, is a popular choice among data teams when it comes to quickly scaling up a data platform.

Building 52

Building BI Data Lake Data Governance 52

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. Confluent Platform 5.2

Kafka 21

Kafka Java Cloud Metadata 21

ProjectPro

JANUARY 19, 2022

Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with. Companies are increasingly substituting physical servers with cloud services, so data engineers need to know about cloud storage and cloud computing.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

AUGUST 11, 2021

Kafka streams, consisting of 500,000 events per second, get ingested into Upsolver and stored in AWS S3. It is also possible to use Snowflake on data stored in cloud storage from Amazon S3 or Azure Data lake for data analytics and transformation. ironSource has to collect and store vast amounts of data from millions of devices.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

NOVEMBER 30, 2021

Cloud: Technology advancements, information security threats, faster internet speeds, and a push to prevent data loss have contributed to the move toward cloud-native storage and processing. You need experience implementing real-time end-to-end projects using big data technologies like Hive, Kafka, Sqoop, etc.,

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

MAY 31, 2021

Services: Cloud Composer, Google Cloud Storage (GCS), Pub-Sub, Cloud Functions, BigQuery, BigTable Big Data Project with Source Code: Build a Scalable Event-Based GCP Data Pipeline using DataFlow 2. Big Data Project using Hadoop with Source Code for Web Server Log Processing 5.

Big Data 52

Big Data Coding Project Hadoop 52