Data Engineering Podcast

MAY 29, 2022

In this episode SVP of engineering Shireesh Thota describes the impact on your overall system architecture that Singlestore can have and the benefits of using a cloud-native database engine for your next application. That’s where our friends at Ascend.io What are the core sets of workloads that SingleStore is aimed at addressing?

Architecture 100

Architecture Database Data Architecture PostgreSQL 100

Snowflake

MARCH 2, 2023

As part of this, we are also supporting Snowpipe Streaming as an ingestion method for our Snowflake Connector for Kafka. This solution is both scalable and reliable, as we have been able to effortlessly ingest upwards of 1GB/s throughput.” How does Snowpipe Streaming work?

Kafka 127

Kafka Data Ingestion Data Pipeline Cloud Storage 127

Snowflake

APRIL 19, 2023

Welcome to the third blog post in our series highlighting Snowflake’s data ingestion capabilities, covering the latest on Snowpipe Streaming (currently in public preview) and how streaming ingestion can accelerate data engineering on Snowflake.

Data Ingestion 59

Data Ingestion Kafka Java Data Pipeline 59

Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Data Science 52

KDnuggets

SEPTEMBER 1, 2023

This article describes a large-scale data warehousing use case to provide reference for data engineers who are looking for log analytic solutions. It introduces the log processing architecture and real-case practice in data ingestion, storage, and queries.

Data Ingestion 123

Data Ingestion Data Engineering Data Engineer Architecture 123

Snowflake

NOVEMBER 11, 2024

What if you could streamline your efforts while still building an architecture that best fits your business and technology needs? Snowflake is committed to doing just that by continually adding features to help our customers simplify how they architect their data infrastructure. Here’s a closer look.

Data Architecture 84

Data Architecture Architecture Data Lake Kafka 84

Rockset

MAY 3, 2023

In scenarios involving analytics on massive data streams, we’re often asked the maximum throughput and lowest data latency Rockset can achieve and how it stacks up to other databases. For this benchmark, we evaluated Rockset and Elasticsearch ingestion performance on throughput and data latency. How did we do it?:

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Knowledge Hut

JULY 3, 2023

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

Cloudyard

MARCH 4, 2023

Read Time: 5 Minute, 16 Second As we know Snowflake has introduced latest badge “Data Cloud Deployment Framework” which helps to understand knowledge in designing, deploying, and managing the Snowflake landscape. Respective Cloud would consume/Store the data in bucket or containers. Snowpipe to automate the ingestion process.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

Hevo

JULY 17, 2024

Every data-centric organization uses a data lake, warehouse, or both data architectures to meet its data needs. Data Lakes bring flexibility and accessibility, whereas warehouses bring structure and performance to the data architecture.

Data Ingestion 52

Data Ingestion Data Lake Data Architecture Architecture 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Snowflake

JANUARY 9, 2024

Data cloud integration: This comprehensive solution begins with the Snowflake Data Cloud as a persistent data layer, which makes data more accessible for organizations to get started with the platform. Data ingestion: Hakkoda leads the entire data ingestion process.

Data Ingestion 110

Data Ingestion Cloud Architecture Accessible 110

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Data ingestion must be performant to handle large amounts of data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Data Engineering Podcast

NOVEMBER 20, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Data Lake 130

Data Lake Data Ingestion MongoDB Google Cloud 130

Cloudera

FEBRUARY 15, 2024

Seeing the future in a modern data architecture The key to successfully navigating these challenges lies in the adoption of a modern data architecture. The promise of a modern data architecture might seem like a distant reality, but we at Cloudera believe data can make what is impossible today, possible tomorrow.

Insurance 91

Insurance Banking Data Architecture Data Ingestion 91

Rockset

OCTOBER 11, 2022

The flow of data often involves complex ETL tooling as well as self-managing integrations to ensure that high volume writes, including updates and deletes, do not rack up CPU or impact performance of the end application. That’s because Elasticsearch can only write data to one index.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Cloudera

NOVEMBER 1, 2023

And so we are thrilled to introduce our latest applied ML prototype (AMP) — a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database. High-level overview of real-time data ingest with Cloudera DataFlow to Pinecone vector database.

Machine Learning 113

Machine Learning Data Ingestion Database Architecture 113

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

AUGUST 11, 2022

And while operations in the cyber-domain are more likely to make the evening news, there are a vast array of critical use cases that support the military’s need for a data architecture that collects, processes, and delivers any type of data, anywhere. . Universal Data Distribution Solves DoD Data Transport Challenges.

Transportation 97

Transportation Data Ingestion Architecture Data 97

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka 105

Kafka Data Ingestion Datasets Architecture 105

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

DECEMBER 9, 2024

Its architecture ensures low-latency, high-availability deployments, making it ideal for enterprise-grade applications. Open and Flexible Platform : With Clouderas open architecture, you can leverage the latest open-source models, avoiding lock-in to proprietary frameworks.

Professional Services 77

Professional Services Data Ingestion Manufacturing Retail 77

The Modern Data Company

JULY 29, 2024

This dramatic increase in vendors hasn’t led to the expected data revolution. Rather, it has created needlessly complex data architectures that are inflexible, resist change, and stifle innovation. It’s a final, frustrating hurdle in the race to become truly data-driven.

Data Architecture 52

Data Architecture Architecture Building Pipeline-centric 52

Ascend.io

JULY 28, 2023

As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Without a well-planned architecture, these pipelines can quickly become unmanageable, often reaching a point where efficiency and transparency take a backseat, leading to operational chaos. What Is Data Pipeline Architecture?

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Cloudera

APRIL 20, 2021

Enterprises usually don’t have the adequate resources to ensure their data streams are protected. What is modern streaming architecture? A modern streaming architecture consists of critical components that provide data ingestion, security and governance, and real-time analytics.

Kafka 98

Kafka Hospitality Retail Data Ingestion 98

Data Engineering Podcast

JUNE 19, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Metadata 130

Metadata MongoDB MySQL Scala 130

Edureka

AUGUST 19, 2024

The Azure Databricks architecture is designed to become an incredibly robust framework in data analytics on the Microsoft Azure platform. High-level Architecture Conclusion Frequently Asked Questions Azure Databricks simplifies the data engineering and data science workflows.

Architecture 40

Architecture Data Lake Machine Learning Data Ingestion 40

Netflix Tech

JANUARY 25, 2023

Marken architecture Above picture represents the block diagram of the architecture for our service. On the left we show data pipelines which are created by several of our client teams to automatically ingest new data into our service. This data is used by various teams for eg.

Algorithm 116

Algorithm Media Metadata Data Ingestion 116

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 84

Data Lake Data Ingestion Bytes Cloud Computing 84

Snowflake

OCTOBER 16, 2024

The company quickly realized maintaining 10 years’ worth of production data while enabling real-time data ingestion led to an unscalable situation that would have necessitated a data lake. Data scientists also benefited from a scalable environment to build machine learning models without fear of system crashes.

Digital Media 83

Digital Media Media Data Lake Data Warehouse 83