Apache Cassandra Lunch #72: Databricks and Cassandra
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The document discusses the integration of Databricks with Cassandra, highlighting its capabilities as a unified platform for data and AI built on lakehouse architecture. It emphasizes features such as SQL analytics, collaborative data science, and production machine learning while positioning Databricks as a fully managed cloud service with strong open source roots. Additional technologies mentioned include TensorFlow, Redash, and a focus on solving engineering and operational challenges.
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Apache Cassandra Lunch #72: Databricks and Cassandra
- 1. Version 1.0 Databricks and Cassandra In Cassandra Lunch #72, we will discuss how we can use Databricks with Cassandra. Arpan Patel Engineer @ Anant
- 2. Databricks ● One unified platform for data and AI built on lakehouse architecture ● Offers free Community Edition (micro-cluster+ cluster manager + notebook environment) ● Reliable data engineering ● SQL Analytics on all your data ● Collaborative data science ● Production machine learning ● Fully managed cloud service -> security, reliability, scaling, and performance ● Rooted in open source -> original creators of Apache Spark, Delta Lake, and MLflow ● Additional technologies -> TensorFlow, Redash, and R
- 3. Demo ● Databricks Community Edition ● DataStax Astra ● Databricks Notebook to do read / writes on Astra
- 4. Strategy: Scalable Fast Data Architecture: Cassandra, Spark, Kafka Engineering: Node, Python, JVM,CLR Operations: Cloud, Container Rescue: Downtime!! I need help. www.anant.us | solutions@anant.us | (855) 262-6826 3 Washington Circle, NW | Suite 301 | Washington, DC 20037