Apache Zeppelin VS Delta Lake

Apache Zeppelin Reviews

Delta Lake Reviews

Apache Zeppelin mentions (7)

• Serverless Apache Zeppelin on AWS

  Now we can proceed with the definition of Apache Zeppelin. It is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with Python, Scala, SQL, Spark, and more. You can execute code and even schedule a job (via cron) to run at regular intervals. - Source: dev.to / 3 months ago

• Visualization using Pyspark Dataframe

  Have you tried Apache Zepellin I remember that you can pretty print spark dataframes directly on it with z.show(df). Source: almost 2 years ago

• Fast CSV Processing with SIMD

  I used to use Zeppelin, some kind of Jupyter Notebook for Spark (that supports Parquet). But it may be better alternatives. https://zeppelin.apache.org/. - Source: Hacker News / over 2 years ago

• What libraries do you use for machine learning and data visualizing in scala?

  Another more widely used notebooks for scala and spark: Https://zeppelin.apache.org/. Source: over 2 years ago

• Dataflow, a self-hosted Observable Notebook Editor

  Apache Zeppelin is one open source option - https://zeppelin.apache.org. - Source: Hacker News / almost 3 years ago

Delta Lake mentions (31)

• Delta Lake vs. Parquet: A Comparison

  Delta is pretty great, let's you do upserts into tables in DataBricks much easier than without it. I think the website is here: https://delta.io. - Source: Hacker News / 4 months ago

• Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog

  Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake. - Source: dev.to / 5 months ago

• [D] Is there other better data format for LLM to generate structured data?

  The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 5 months ago

• Databricks Strikes $1.3B Deal for Generative AI Startup MosaicML

  Databricks provides Jupyter lab like notebooks for analysis and ETL pipelines using spark through pyspark, sparkql or scala. I think R is supported as well but it doesn't interop as well with their newer features as well as python and SQL do. It interfaces with cloud storage backend like S3 and offers some improvements to the parquet format of data querying that allows for updating, ordering and merged through... - Source: Hacker News / 10 months ago

• The "Big Three's" Data Storage Offerings

  Structured, Semi-structured and Unstructured can be stored in one single format, a lakehouse storage format like Delta, Iceberg or Hudi (assuming those don't require low-latency SLAs like subsecond). Source: 11 months ago