Rockset

AUGUST 30, 2021

A Quick Primer on Indexing in Rockset Rockset allows users to connect real-time data sources — data streams (Kafka, Kinesis), OLTP databases (DynamoDB, MongoDB, MySQL, PostgreSQL) and also data lakes (S3, GCS) — using built-in connectors. You already know how to use Rockset because you know how to use SQL.

SQL 52

SQL Kafka MongoDB MySQL 52

Netflix Tech

JULY 26, 2021

Change Data Capture(CDC) source connector reads from studio applications’ database transaction logs and emits the change events. The CDC events are passed on to the Data Mesh enrichment processor, which issues GraphQL queries to Studio Edge to enrich the data. CDC events can also be sent to Data Mesh via a Java Client Producer Library.

Data 101

Data Data Pipeline MySQL Data Warehouse 101

Netflix Tech

AUGUST 1, 2022

We will deliver a series of articles that cover different aspects of Data Mesh and what we have learned from our journey. Data Mesh Overview A New Definition Of Data Mesh Previously, we defined Data Mesh as a fully managed, streaming data pipeline product used for enabling Change Data Capture (CDC) use cases.

Process 108

Process Transportation Kafka Entertainment 108

Rockset

MARCH 26, 2023

The concept of Change Data Capture (CDC) has been around for a while but specific solutions have taken many shapes. The most recent of these, and potentially the most interesting, is real-time CDC enabled by the same internal database logging systems used to build tables.

Cloud 52

Cloud PostgreSQL Kafka Database 52

Rockset

MAY 10, 2022

To overcome this, Change Data Capture (CDC) techniques are often used to copy changes from the NoSQL database into an analytics database where analysts can perform more computationally heavy tasks across larger datasets. In this post, we’ll look at how CDC works with DynamoDB and its potential use cases.

NoSQL 52

NoSQL AWS MongoDB Datasets 52

Cloudera

AUGUST 10, 2022

We are now launching Cloudera Stream Processing Community Edition (CSP-CE), which makes all of these tools and technologies readily available for developers and anyone who wants to experiment with them and learn about stream processing, Kafka and friends, Flink, and SSB.

Process 86

Process Kafka PostgreSQL MySQL 86

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 96

Architecture Building Kafka Database-centric 96

Monte Carlo

OCTOBER 17, 2022

The organizations and the target/source systems were different—the first was a Qubole data platform to AWS EMR and Athena migration at Mapbox, the second which is currently ongoing at Unbounce is a MySQL to AWS Redshift—but the process and best practices were remarkably similar. Have fun and good luck with your data warehouse migration!

Data Warehouse 59

Data Warehouse AWS MySQL Data 59

Knowledge Hut

JULY 24, 2023

As big data and machine learning have become more prevalent, SQL is increasingly being used to train and query predictive models, which may help businesses make better decisions. Most database management systems, such as Microsoft SQL Server, MySQL, and SAP Adaptive Server, are compatible with SQL.

SQL 52

SQL Database Process NoSQL 52

ProjectPro

FEBRUARY 8, 2023

Furthermore, Glue supports databases hosted on Amazon Elastic Compute Cloud (EC2) instances on an Amazon Virtual Private Cloud, including MySQL, Oracle, Microsoft SQL Server, and PostgreSQL. Create a dynamic, efficient, and automatic machine learning workflow with AWS Cloud for this wildfire analytics big data project.

AWS 98

AWS Scala Metadata Data Lake 98

Rockset

JUNE 7, 2022

Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. DynamoDB uses a variable pricing model where you pay for what you use, which is based on a throughput model with additional charges for features like backup and restore, on-demand capacity, streams, change data capture (CDC) and others.

MongoDB 52

MongoDB NoSQL Non-relational Database Relational Database 52