Software Alternatives & Reviews

Apache Spark VS Azure Databricks

Compare Apache Spark VS Azure Databricks and see what are their differences

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Azure Databricks logo Azure Databricks

Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Azure Databricks Landing page
    Landing page //
    2023-04-02

Apache Spark videos

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Azure Databricks videos

Azure Databricks is Easier Than You Think

More videos:

  • Review - Ingest, prepare & transform using Azure Databricks & Data Factory | Azure Friday
  • Review - Azure Databricks - What's new! | DB102

Category Popularity

0-100% (relative to Apache Spark and Azure Databricks)
Databases
100 100%
0% 0
Technical Computing
0 0%
100% 100
Big Data
100 100%
0% 0
Business & Commerce
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Spark and Azure Databricks

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...

Azure Databricks Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Azure Databricks is a data analytics tool optimized for Microsoft’s Azure cloud services solution. It provides three development environments for data-intensive apps, namely Databricks SQL, Databricks Machine Learning, and Databricks Data Science & Engineering.The platform supports languages including Python, Java, R, Scala, and SQL, plus data science frameworks and...
Source: theqalead.com

Social recommendations and mentions

Based on our record, Apache Spark seems to be a lot more popular than Azure Databricks. While we know about 56 links to Apache Spark, we've tracked only 2 mentions of Azure Databricks. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

Azure Databricks mentions (2)

  • Top 30 Microsoft Azure Services
    In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 3 years ago
  • ZooKeeper-free Kafka is out. First Demo
    https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 3 years ago

What are some alternatives?

When comparing Apache Spark and Azure Databricks, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

MicroStrategy - MicroStrategy is a cloud-based platform providing business intelligence, mobile intelligence and network applications.

Hadoop - Open-source software for reliable, scalable, distributed computing

Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.