Lyft Engineering

NOVEMBER 29, 2023

Introduction At Lyft, we have used systems like Apache ClickHouse and Apache Druid for near real-time and sub-second analytics. In this particular blog post, we explain how Druid has been used at Lyft and what led us to adopt ClickHouse for our sub-second analytic system. An example of how we use Druid rollup at Lyft.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Confluent

MAY 30, 2019

Following part 1 and part 2 of the Spring for Apache Kafka Deep Dive blog series, here in part 3 we will discuss another project from the Spring team: Spring Cloud Data Flow , which focuses on enabling developers to easily develop, deploy, and orchestrate event streaming pipelines based on Apache Kafka ®.

Kafka 94

Kafka Cloud Data Pipeline PostgreSQL 94

Rockset

MARCH 27, 2023

This blog will clarify some conceptual differences, provide an overview of popular tools, and offer a framework for deciding which tools are best suited for specific technical requirements. This is part two in Rockset’s Making Sense of Real-Time Analytics on Streaming Data series. With that, let’s dive in. So do you need just one?

Database 52

Database Process Scala SQL 52

Picnic Engineering

SEPTEMBER 8, 2022

In the “Picnic Analytics Platform: Migration from AWS Kinesis to Confluent Cloud” we described why and how we migrated from AWS Kinesis to Confluent Cloud. Our pipeline captures these events and sends them to Confluent Cloud. We use the RabbitMQ Source connector for Apache Kafka Connect.

Kafka 52

Kafka Metadata AWS Java 52

Confluent

JULY 31, 2019

Delivers the new Confluent Operator for cloud-native automation on Kubernetes, a redesigned Confluent Control Center user interface to simplify how you manage event streams, and a preview of Role-Based Access Control for enterprise-grade security. To solve these challenges, Confluent Platform 5.3

Kafka 19

Kafka Cloud Accessible Accessibility 19

Confluent

MAY 9, 2019

Pillar 4 – Operational plane: Event logging, DLQs and automation. Yes, we can transact across partitions in Apache Kafka ® , and with traditional database transactions you get many “trust” semantics for free; however, they are pushed down into the database runtime. Four pillars of event streaming. Putting it all together.

Kafka 93

Kafka Pipeline-centric Architecture Database-centric 93

Confluent

FEBRUARY 13, 2019

Rather, we apply different event planes to provide orthogonal aspects of system design such as core functionality, operations and instrumentation. Rather, we apply different event planes to provide orthogonal aspects of system design such as core functionality, operations and instrumentation. Event-driven architecture. Data evolution.

Architecture 90

Architecture Programming Kafka Database-centric 90