Executive SummaryUpdated on Dec 17, 2024
Databricks and Apache Spark Streaming compete in the data analytics and machine learning space. Databricks holds an advantage with its comprehensive cloud integration and built-in optimizations, while Apache Spark Streaming excels in open-source, real-time data processing.
Features: Databricks is favored for its built-in optimization and Delta data format, which enhances performance. It offers seamless integration with Spark and Python, making it ideal for machine learning and big data. Its flexibility in supporting multiple programming languages also makes it attractive. Apache Spark Streaming is notable for its real-time data processing capabilities and low-latency performance. Its versatility and open-source nature with Python support are key highlights.
Room for Improvement: Databricks needs to enhance its visualization capabilities and expand integration options. There is also a need to expand its machine learning features and improve user interfaces for non-technical users. Apache Spark Streaming could improve its memory management and real-time analytics capabilities. Enhancements in event-level integration and interface user-friendliness are needed.
Ease of Deployment and Customer Service: Databricks provides deployment across public and private clouds with robust technical support, although response times could be better. Microsoft support is available as part of enterprise solutions. Apache Spark Streaming is typically deployed in public clouds, where documentation often suffices, but open-source community support varies in availability and responsiveness.
Pricing and ROI: Databricks is seen as expensive, particularly for non-batch applications, but offers significant ROI through scalability and integration. Its comprehensive feature set justifies the cost. Apache Spark Streaming, being open-source, offers a more affordable solution with expenses mainly associated with cloud use and optional commercial support, resulting in higher ROI due to lower initial costs.
To learn more, read our detailed
Apache Spark Streaming vs. Databricks Report (Updated: December 2024).
