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- Azure Data Lake Analytics-vs-Azure Databricks
Compare Azure Data Lake Analytics and Azure Databricks 
- Users report that Azure Databricks excels in real-time analytics with a score of 8.8, while Azure Data Lake Analytics has a lower score of 8.1, indicating that Databricks may be better suited for applications requiring immediate data insights.
- Reviewers mention that Azure Databricks offers superior data querying capabilities, scoring 9.3 compared to Azure Data Lake Analytics' 8.8, which suggests that users may find Databricks more efficient for complex data queries.
- G2 users highlight that Azure Databricks provides a more robust Spark integration with a score of 9.0, while Azure Data Lake Analytics scores slightly lower at 8.6, making Databricks a better choice for users heavily invested in Spark-based workflows.
- Users on G2 report that Azure Databricks shines in multi-source analysis with a score of 9.0, compared to Azure Data Lake Analytics' 7.9, indicating that Databricks may be more effective for users needing to analyze data from various sources.
- Reviewers mention that Azure Databricks offers a more user-friendly experience with an ease of use score of 8.6, slightly higher than Azure Data Lake Analytics' score of 8.4, suggesting that Databricks may be easier for new users to adopt.
- Users say that Azure Databricks provides better support for notebooks, scoring 9.3, while Azure Data Lake Analytics scores 8.2, indicating that Databricks may be more appealing for users who rely on interactive notebooks for data analysis.
Easy to get started with Data Lake, and build on structured/unstructured data sets using data lake analytics. The data lake analytics tool is transformation rich, and provides loads of compute power to speed up processing times (without load contingencies)
Maintenance charges for hourly basis when spinning up.
As a person who is working in the data field, it's a very important tool in my day-to-day life. I tried with a lot of platforms such as ubuntu to install Pyspark and work with data. But the benefit of azure data bricks is that is simplicity. A user-friendly...
Despite having many features and guides, the Azure Databricks team does not offer any guidance for deploying new features or upgrading versions.
Easy to get started with Data Lake, and build on structured/unstructured data sets using data lake analytics. The data lake analytics tool is transformation rich, and provides loads of compute power to speed up processing times (without load contingencies)
As a person who is working in the data field, it's a very important tool in my day-to-day life. I tried with a lot of platforms such as ubuntu to install Pyspark and work with data. But the benefit of azure data bricks is that is simplicity. A user-friendly...
Maintenance charges for hourly basis when spinning up.
Despite having many features and guides, the Azure Databricks team does not offer any guidance for deploying new features or upgrading versions.
