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Druid Deprecation and ClickHouse Adoption at Lyft

Lyft Engineering

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.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

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.

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Using other CDP services with Cloudera Operational Database

Cloudera

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 .

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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.

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Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset

Rockset

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.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

However, you can also pull data from centralized data sources like data warehouses to transform data further and build ETL pipelines for training and evaluating AI agents. Processing: It is a data pipeline component that decides the data flow implementation.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.