article thumbnail

Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

Traditional Data Processing: Batch and Streaming MapReduce, most commonly associated with Apache Hadoop, is a pure batch system that often introduces significant time lag in massaging new data into processed results. A common implementation would have large batch jobs in Hadoop complemented by an update stream stored in Apache Kafka.

article thumbnail

Building A Data Lake For The Database Administrator At Upsolver

Data Engineering Podcast

Summary Data lakes offer a great deal of flexibility and the potential for reduced cost for your analytics, but they also introduce a great deal of complexity. In order to bring the DBA into the new era of data management the team at Upsolver added a SQL interface to their data lake platform.

Data Lake 100
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Data Ingestion: 7 Challenges and 4 Best Practices

Monte Carlo

Data from these sources are often ingested into a cloud-based data warehouse or data lake , where they can then be mined for information and insights. Source : Fundamentals of Data Engineering by Joe Reis and Matt Housley. Some data teams will leverage micro-batch strategies for time sensitive use cases.

article thumbnail

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. Finally, the data is published and visualized on a Java-based custom Dashboard. This is called Hot Path.