Data Engineering Podcast

NOVEMBER 18, 2018

Summary Modern applications and data platforms aspire to process events and data in real time at scale and with low latency. How does Flink compare to other streaming engines such as Spark, Kafka, Pulsar, and Storm? How do you handle out of order events in Flink, especially as the delay for a given event increases?

Process 100

Process Google Cloud Scala Kafka 100

Rockset

AUGUST 21, 2019

Rockset continuously ingests data streams from Kafka, without the need for a fixed schema, and serves fast SQL queries on that data. We created the Kafka Connect Plugin for Rockset to export data from Kafka and send it to a collection of documents in Rockset. Implementing a working plugin What is Kafka Connect and Confluent Hub?

Kafka 40

Kafka IT Data Storage Relational Database 40

Rockset

MARCH 26, 2023

Breaking Bad… Data Silos We haven’t quite figured out how to avoid using relational databases. Folks have definitely tried, and while Apache Kafka® has become the standard for event-driven architectures, it still struggles to replace your everyday PostgreSQL database instance in the modern application stack.

Cloud 52

Cloud PostgreSQL Kafka Database 52

Rockset

OCTOBER 11, 2022

Logstash is an event processing pipeline that ingests and transforms data before sending it to Elasticsearch. Logstash offers a JDBC input plugin that polls a relational database, like PostgreSQL or MySQL, for inserts and updates periodically. The connector does require installing and managing additional tooling, Kafka Connect.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Precisely

JANUARY 25, 2024

It frequently also means moving operational data from native mainframe databases to modern relational databases. Typically, a mainframe to cloud migration includes re-factoring code to a modern object-oriented language such as Java or C# and moving to a modern relational database. Best Practice 5.

Metadata 69

Metadata Relational Database Data Governance Government 69

Cloudera

NOVEMBER 2, 2020

Ingest 100s of TB of network event data per day . real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). Several billion ad impression events per day are streamed in and stored. Time Series and Event Analytics Specialized RTDW. 200,000 queries per day.

Data Warehouse 95

Data Warehouse Kafka Lambda Architecture Telecommunication 95

Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. Upcoming events include the Software Architecture Conference in NYC and PyCOn US in Pittsburgh.

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

LinkedIn Engineering

JANUARY 16, 2024

At the heart of this system was a reliance on a relational database, Oracle, which served as the repository for all member restrictions data. Figure 2: Relational database schema We adopted a pragmatic and scalable approach by distributing member restrictions across different Oracle tables.

Kafka 84

Kafka Relational Database Java Database 84

Confluent

JUNE 18, 2019

Using SQL to run your search might be enough for your use case, but as your project requirements grow and more advanced features are needed—for example, enabling synonyms, multilingual search, or even machine learning—your relational database might not be enough. Building an indexing pipeline at scale with Kafka Connect.

Architecture 97

Architecture Building Kafka Database-centric 97

Confluent

AUGUST 20, 2019

Traditional relational database systems are ubiquitous in software systems. They are surrounded by a strong ecosystem of tools, such as object-relational mappers and schema migration helpers. A tomicity in relational databases ensures that a transaction either succeeds or fails as a whole.

Kafka 22

Kafka Systems Building Relational Database 22

Cloudera

MARCH 23, 2023

This allows business users to define events of interest for which they need to continuously monitor and respond quickly. Imagine, for instance, that we have a real-time Kafka stream containing plane data and we are working on an application that needs to download all planes in a certain area, above some altitude at any given time via REST.

SQL 80

SQL Kafka PostgreSQL Database 80

Confluent

OCTOBER 10, 2019

Apache Kafka ® and its surrounding ecosystem, which includes Kafka Connect, Kafka Streams, and KSQL, have become the technology of choice for integrating and processing these kinds of datasets. Use cases for IoT technologies and an event streaming platform. Example: Severstal.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

Knowledge Hut

APRIL 25, 2024

NoSQL databases are designed for scalability and flexibility, making them well-suited for storing big data. The most popular NoSQL database systems include MongoDB, Cassandra, and HBase. In general, Hadoop and Spark are good choices for batch processing, while Kafka and Storm are better suited for streaming applications.

Big Data 98

Big Data Technology Hadoop NoSQL 98

Confluent

SEPTEMBER 25, 2019

What’s forgotten is that the rise of this paradigm was driven by a particular type of human-facing application in which a user looks at a UI and initiates actions that are translated into database queries. Because databases don’t model the flow of data, the interconnection between systems in a company is a giant mess. What is an event?

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

Knowledge Hut

JULY 24, 2023

According to recent studies, the global database market will grow from USD 63.4 SQL is a powerful tool for managing and manipulating relational databases, and it continues to be widely used in the industry today. Traditional databases need to be optimized to handle complex event processing. billion in 2022 to $154.6

Database 52

Database SQL Process NoSQL 52

LinkedIn Engineering

MAY 11, 2023

We leveraged Iris -based alerting and an internally available event bus through which SREs could know the state of their submissions without continually interacting with the API. For MaaS, the starting point was co-hosting the web service, relational database ( Postgres ), and Redis -based caching layer on a server.

Management 101

Management PostgreSQL MySQL Kafka 101

Netflix Tech

NOVEMBER 4, 2019

Luckily, we have Kafka events that are emitted each time a piece of data changes. The first step is to listen to those events and act accordingly. When our indexer hears a change event it needs to find all the creatives that are affected and reindex them. The indexer needs to know when changes happen. Search Indexer.

Kafka 97

Kafka Algorithm Database Relational Database 97

Data Engineering Weekly

DECEMBER 18, 2022

link] Percona: JSON and Relational Databases – Part One Whether we like it or not, most data engineering and modeling challenges will be handling semi-structured data in the coming years. The Percona blog walkthrough JSON support in the relational databases. Streaming plus batch unified in a single platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Relational Database 52

AltexSoft

SEPTEMBER 23, 2021

The structure of data is usually predefined before it is loaded into a warehouse, since the DW is a relational database that uses a single data model for everything it stores. In a nutshell, a model is a specific data structure a database can ingest. Enrichment helps us increase the value of data by adding extra-context.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Knowledge Hut

NOVEMBER 19, 2023

Open Source Support: Many Azure services support popular open-source frameworks like Apache Spark, Kafka, and Hadoop, providing flexibility for data engineering tasks. These patterns can be used to start workflows, trigger events, or create alerts, as well as to feed data into reporting tools or store altered data for later use.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

AltexSoft

MAY 14, 2021

This data isn’t just about structured data that resides within relational databases as rows and columns. The analytics commonly takes place after a certain period of time or event. Outlier analysis or anomaly detection is the technique used to identify data points and events that deviate from the rest of the data.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 PostgreSQL 14 – Sometimes I forget, but traditional relational databases play a big role in the lives of data engineers. And of course, PostgreSQL is one of the most popular databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 PostgreSQL 14 – Sometimes I forget, but traditional relational databases play a big role in the lives of data engineers. And of course, PostgreSQL is one of the most popular databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

ProjectPro

JANUARY 25, 2022

PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDDs are also fault-tolerant; thus, they will automatically recover in the event of a failure. RDD is an acronym for- Resilient - It is fault-tolerant and capable of regenerating data in the event of a failure.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

JUNE 7, 2021

Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Another available schema — DataFrames — is used to organize information in the named columns, similar to tables in relational databases. Complex programming environment.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Rockset

MARCH 27, 2023

Streams”, as opposed to tables in a relational database context, are the first-class citizens in stream processing. Stream processing approximates something like a continuous query; each event that passes through the system is analyzed according to pre-defined criteria and can be consumed by other systems.

Database 52

Database Process Scala SQL 52

Rockset

APRIL 15, 2021

Relational databases today are widely known to be suboptimal for supporting high-scale analytical use cases, and are all but certain to run into issues as your production data size and query volume grow. Compute and storage are also separately scaled in Rockset, allowing you to cost-optimize for the desired performance of your choice.

PostgreSQL 40

PostgreSQL MySQL Relational Database NoSQL 40

Grouparoo

OCTOBER 6, 2021

55 Pipe Dreams Kafka was good because it had replaying of messages. 55 Pipe Dreams Kafka was good because it had replaying of messages. 69 The End of ETL as We Know It Use events from the product to notify data systems of changes. If so, find a way to abstract the silos to have one way to access it all.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

ProjectPro

DECEMBER 7, 2021

The big data pipeline must process data in large volumes concurrently because, in reality, multiple big data events are likely to occur at once or relatively close together. Consequently, data engineers implement checkpoints so that no event is missed or processed twice. It not only consumes more memory but also slackens data transfer.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Confluent

SEPTEMBER 19, 2019

When people ask me the very top-level question “why do people use Kafka,” I usually lead with the story in my last post , where I talked about how Apache Kafka ® is helping us deliver on the promises the cloud made to us a decade ago. Industry heavyweights like Capital One use event streaming on Kafka for this very task.

Kafka 14

Kafka Data Pipeline Bytes Data Architect 14

Edureka

FEBRUARY 9, 2023

Apache Kafka: Apache Kafka is a decentralized publish-subscribe messaging system designed to handle data streams with high volume, high throughput, and low latency. It is ideal for use cases such as real-time data processing, data streaming, and event-driven architectures because it allows multiple consumers to read data concurrently.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data 52

Big Data Project Metadata Programming Language 52

Netflix Tech

DECEMBER 17, 2019

In databases like MySQL and PostgreSQL, transaction logs are the source of CDC events. There are several open source CDC projects, often using the same underlying libraries, database APIs, and protocols. Some of DBLog’s features are: Processes captured log events in-order. Providing high availability for real-time events.

MySQL 87

MySQL PostgreSQL Database Transportation 87

Netflix Tech

DECEMBER 17, 2019

In databases like MySQL and PostgreSQL, transaction logs are the source of CDC events. There are several open source CDC projects, often using the same underlying libraries, database APIs, and protocols. Some of DBLog’s features are: Processes captured log events in-order. Providing high availability for real-time events.

MySQL 81

MySQL PostgreSQL Database Transportation 81

Netflix Tech

NOVEMBER 4, 2019

Luckily, we have Kafka events that are emitted each time a piece of data changes. The first step is to listen to those events and act accordingly. When our indexer hears a change event it needs to find all the creatives that are affected and reindex them. The indexer needs to know when changes happen. Search Indexer.

Kafka 45

Kafka Algorithm Database Relational Database 45

Rockset

OCTOBER 20, 2021

For instance, let’s say you have streaming data coming in from Kafka or Kinesis. S3 or GCS), NoSQL databases (e.g. DynamoDB or MongoDB), and relational databases (e.g. Incremental materializations are usually best suited for event or time-series data streamed directly into Rockset. PostgreSQL or MySQL).

SQL 52

SQL PostgreSQL MongoDB NoSQL 52

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. SQL Proficiency : SQL (Structured Query Language) is fundamental for working with databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52