Data Engineering Podcast

JANUARY 21, 2024

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Find simplicity in your most complex projects with Miro.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Weekly

FEBRUARY 18, 2025

Kafka is designed for streaming events, but Fluss is designed for streaming analytics. Architecture Difference The first difference is the Data Model. The fourth difference is the Lakehouse Architecture. Fluss embraces the Lakehouse Architecture. How do you compare Fluss with Apache Kafka?

Kafka 74

Kafka Lambda Architecture SQL Architecture 74

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM!

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

Towards Data Science

JANUARY 16, 2024

New data formats emerged — JSON, Avro, Parquet, XML etc. Data lakes were introduced to store the new data formats. Image by the author 2010 to 2020 - The Cloud Data Warehouse Enterprises now wanted quick data analytics without yesterday’s constraints of flexibility, processing power and scale.

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

Striim

AUGUST 22, 2024

Real-Time Analytics Architecture When implementing real-time analytics, you’ll need a different architecture and approach than you would with traditional batch-based data analytics. The streaming and processing of large volumes of data will also require a unique set of technologies.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Edureka

FEBRUARY 7, 2023

One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It does away with the requirement to import data from an outside source. Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Rockset

MARCH 19, 2020

With all of these stream processing and real-time data store options, though, also comes questions for when each should be used and what their pros and cons are. I hope by the end you find yourself better informed and less confused about the real-time analytics landscape and are ready to dive in to it for yourself.

Kafka 40

Kafka Database Process SQL 40