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 104

Kafka Data Ingestion Datasets Architecture 104

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Python Kafka Java 106

Cloudera

FEBRUARY 16, 2021

In the following sections, we see how the Cloudera Operational Database is integrated with other services within CDP that provide unified governance and security, data ingest capabilities, and expand compatibility with Cloudera Runtime components to cater to your specific use cases. . Integrated across the Enterprise Data Lifecycle .

Database 83

Database Machine Learning Data Lake Kafka 83

Rockset

APRIL 18, 2023

Under the hood, Rockset utilizes its Converged Index technology, which is optimized for metadata filtering, vector search and keyword search, supporting sub-second search, aggregations and joins at scale. Feature Generation: Transform and aggregate data during the ingest process to generate complex features and reduce data storage volumes.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

ProjectPro

DECEMBER 7, 2021

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. Data ingestion methods gather and bring data into a data processing system.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. Because of its interoperability, it is the best framework for processing large datasets.

Big Data 52

Big Data Data Process Process Kafka 52