Data Engineering Podcast

MARCH 3, 2024

Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. What are the key considerations for powering AI applications that are substantially different from analytical applications?

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

AltexSoft

SEPTEMBER 23, 2021

This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. Data hub architecture. Data hub architecture.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Cloudera

MAY 30, 2024

This unified data environment eliminates the need for maintaining separate data silos and facilitates seamless access to data for AI and analytics applications. Support for Modern Analytics Workloads : With support for both SQL-based querying and advanced analytics frameworks (e.g.,

Data Lake 63

Data Lake Data Warehouse Programming Language Data Ingestion 63

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. The high-level architecture shown below forms the backdrop for the exploration.

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Cloudera

NOVEMBER 7, 2023

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? Most traditional analytics applications like Hive, Spark, Impala, YARN etc. Protocols provided by Ozone: ofs ofs is a Hadoop Compatible File System (HCFS) protocol.

Systems 103

Systems Hadoop Unstructured Data Media 103

Rockset

JANUARY 30, 2024

In 2023, Rockset announced a new cloud architecture for search and analytics that separates compute-storage and compute-compute. With this architecture, users can separate ingestion compute from query compute, all while accessing the same real-time data. This is a game changer in disaggregated, real-time architectures.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Rockset

OCTOBER 26, 2023

BlueML has been central to supporting LLM-based applications and JetBlue’s AI & ML real-time products. The architecture for JetBlue chatbots using OpenAI and Rockset. With a cloud architecture, each application has its own isolated compute cluster to eliminate resource contention across applications and save on storage costs.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

Christophe Blefari

MARCH 24, 2023

LinkedIn team decided to migrate to a lambda architecture and got 94% uplift in performance. Hex is a notebook-based analytics application. Cells are at the center of the analytics, they produce outputs than can be used later in other cells on in visualisation. How fast is DuckDB really?

Lambda Architecture 130

Lambda Architecture Data Pipeline Data SQL 130

Cloudera

SEPTEMBER 15, 2022

A unified storage architecture that can store both files and objects and provide a flexible, scalable, and high-performance system. Apache Ozone achieves this significant capability through the use of some novel architectural choices by introducing bucket type in the metadata namespace server. Bucket types. release version.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Data Engineering Podcast

MARCH 20, 2022

Can you describe a typical end-to-end architecture where Pinot will be used for embedded analytics? What are some heuristics that you have developed for understanding how to manage data lifecycles in a user-facing analytics application? Can you describe how Pinot is architected? data tiering, tail latencies, etc.)

Datasets 100

Datasets Kafka Analytics Application SQL 100

Rockset

JUNE 21, 2022

We’re excited to announce that Rockset’s new connector with Snowflake is now available and can increase cost efficiencies for customers building real-time analytics applications. To learn how Rockset architecture enables fast, compute-efficient analytics on real-time data, read more about Rockset Concepts, Design & Architecture.

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Cloudera

DECEMBER 1, 2022

For analytic applications to properly leverage a hybrid, multi-cloud ecosystem to support modern data architectures, data observability has become even more important. Ramsey International Modern Data Platform Architecture. I spoke to Mark Ramsey of Ramsey International (RI) to dive deeper into that last subject.

Data Lake 83

Data Lake Data Pipeline Data Governance Analytics Application 83

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Change data capture (CDC) streams from OLTP databases, which may provide sales, demographic or inventory data, are another valuable source of data for real-time analytics use cases. Flink, Kafka and MySQL.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Rockset

MARCH 3, 2022

This data has material financial value when it’s both fresh and easy to access, however, customers commonly face scalability challenges running both transactional and analytical applications on the same database. Transactional databases must be write-optimized and analytical applications require low-latency reads.

Amazon Web Services 52

Amazon Web Services Data Warehouse SQL AWS 52

Towards Data Science

APRIL 26, 2023

Whether you work in BI, Data Science or ML all that matters is the final application and how fast you can see it working end-to-end. Imagine, as a practical example, that we need to build a new customer-facing analytics application for our product team. General architecture of our system.

Engineering 67

Engineering Data Lake AWS BI 67

Knowledge Hut

MARCH 29, 2024

Components Of Microsoft Azure Architecture Here are some of the components of Microsoft Azure Architecture are mentioned below: 1. Monitoring and Logging: Discuss how to track and analyze resource utilization and performance using Log Analytics, Application Insights, and Azure Monitor.

Cloud Computing 52

Cloud Computing SQL Database Accessible 52

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. With these results, we show that it is possible for a disaggregated cloud architecture to support search and analytics on high-velocity streaming data.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Cloudera

NOVEMBER 22, 2021

In addition, how can we enable different application development teams to efficiently collaborate and apply agile DevOps disciplines when they leverage different programming constructs (e.g., different analytical frameworks) for complex use cases that span different stages across the data lifecycle? public, private, hybrid cloud)?

Government 92

Government Hadoop Data Security Data Warehouse 92

Cloudera

AUGUST 13, 2021

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. What is the impact on the business?

Data Pipeline 109

Data Pipeline Data Lake ETL Tools Unstructured Data 109

Snowflake

FEBRUARY 7, 2023

The resulting changes to business models and basic technologies spawned next-generation capabilities for practically every category of software, including product analytics. Next-gen product analytics is now warehouse-native, an architectural approach that allows for the separation of code and data.

BI 81

BI Building ETL Tools Data Warehouse 81

Knowledge Hut

MAY 3, 2024

With RStudio, it makes a killer statistic, plotting, and data analytics application. Let’s understand architecture in a little depth to understand the performance implications of using these languages. JVM compatible Application Execution Flow Consider the applications written are JVM compatible (Java/Scala).

Scala 52

Scala Java Python Programming Language 52

Rockset

JULY 6, 2022

I invite you to learn more about how Rockset’s architecture offers the best of traditional and modern — SQL and NoSQL — schemaless data ingestion with automatic schematization. This architecture fully empowers complex queries and will satisfy the requirements of the most demanding real-time data applications with surprising efficiency.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Cloudera

FEBRUARY 8, 2024

The support for Apache Iceberg as the table format in Cloudera Data Platform and the ability to create and use materialized views on top of such tables provides a powerful combination to build fast analytic applications on open data lake architectures.

Metadata 90

Metadata Data Warehouse BI AWS 90

AltexSoft

OCTOBER 21, 2022

The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies. Kafka architecture. Kafka cluster architecture. Or stay here to make sense of Kafka’s concepts and structure.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines?

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Basic Architecture for Real-Time Data Warehousing. These include stream processing/analytics, batch processing, tiered storage (i.e.

Data Warehouse 94

Data Warehouse Kafka Lambda Architecture Telecommunication 94

AltexSoft

JULY 18, 2023

This article will expose Apache Spark architecture, assess its advantages and disadvantages, compare it with other big data technologies, and provide you with the path to learning this impactful instrument. Two key abstractions in Spark architecture are the Resilient Distributed Dataset (RDD) and the Directed Acyclic Graph (DAG).

Big Data 52

Big Data Data Process Process Hadoop 52

Cloudera

SEPTEMBER 1, 2020

It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e.

Cloud Storage 68

Cloud Storage Unstructured Data AWS Analytics Application 68

Rockset

FEBRUARY 9, 2023

Background The single table design for DynamoDB simplifies the architecture required for storing data in DynamoDB. Instead of having multiple tables for each record type you can combine the different types of data into a single table. This works because DynamoDB is able to store very wide tables with varying schema.

Designing 52

Designing Transportation SQL Utilities 52

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. Rockset is designed for real-time analytics. Rockset uses an architecture called Aggregator Leaf Tailer (ALT).

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Kafka or Kinesis ? Stream processing or an OLAP database? Open source or fully managed?

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Rockset

MARCH 15, 2021

The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e., and your solution will only be able to provide valuable real-time analytics if you are able to meet them. Indexing Efficiency Indexing data is another crucial requirement for real-time analytics applications.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Knowledge Hut

JUNE 30, 2023

Master the art of data modeling and developing scalable data architectures. With helpful illustrations and thorough explanations, it assists readers in comprehending how to use Spark for big data processing and analytics applications. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Rockset

AUGUST 18, 2020

This means the lines between real-time analytics and real-time analytical applications are now blurring. Live dashboards that alert humans to take actions and online applications that automatically trigger the right actions are both in the realm of real-time analytics.

Data Lake 40

Data Lake Data Schemas BI Kafka 40

Knowledge Hut

JUNE 26, 2023

A complete end-to-end stream processing pipeline is shown here using an architectural diagram. This project's architecture is essentially composed on five layers: the Data Ingestion layer, the Message broker layer, the Stream processing layer, the Serving database layer, and the Visualisation layer.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

JUNE 16, 2023

Data Engineer Data engineers are engineers responsible for creating reliable architecture and interface designs to collect and transform data from various sources.

Data Analytics 52

Data Analytics Business Analyst Business Intelligence Consulting 52