Databricks Lakehouse is modern solutions for current big data problems
July 07, 2021

Databricks Lakehouse is modern solutions for current big data problems

Surendranatha Reddy Chappidi | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with Databricks Lakehouse Platform (Unified Analytics Platform)

Databricks Lakehouse platform is used across all departments in my current organization.
It is used as part of solving different data engineering and data analytics use cases in different teams.
Databricks Lakehouse platform provides seamless integration with Azure cloud in Maersk. Databricks Lakehouse platform uses spark, mlops, delta for slovong the recent big data engineering problems.
  • Seamless integration with Azure cloud platform services like Azure Data Lake Storage, Blobstorage , Azure Data Factory, Azure DevOps.
  • Databricks lakehouse platform in backed uses Apache Spark for all the computation to be faster and distributed. It helps to complete data pipelines to process huge amounts [of] big data in lesser time with low cost.
  • Databricks Lakehouse solves the problems data lake, by introducing Delta Lake concept. It provides support for updates, deletes, schema evaluation.
  • Databricks Lakehouse platform can provide better platform for managing, and monitoring the cluster performance, utilization, optimization suggestions. It helps developers to leverage those insights for building better data pipelines.
  • Databricks Lakehouse platform can provide GUI version to create spark jobs by click, drag and drop. That reduces the significant amount of time to develop code.
  • Databricks Lakehouse platform can provide better insights and details regarding the jobs failures and resources consumption
  • Spark process framework
  • Delta Lake support
  • Seamless integration with Azure Cloud
  • Making the data available from new data sources which were not available previously
  • Reduced the data granularity and availability from 24 hours to 15 minutes, so that business leaders and stakeholders can take better and faster decisions
Databricks provides support for CURD operations by introducing Delta Lake file format.
Cloudera doesn't have support for the same.

Databricks Lakehouse platform provides different interfaces for data analysts, data engineers and data scientists.
Databricks Lakehouse platform provides seamless integration with different cloud platforms like Azure and AWS.
Cost-wise Azure Lakehouse platform is better than Cloudera.

Do you think Databricks Lakehouse Platform (Unified Analytics Platform) delivers good value for the price?

Yes

Are you happy with Databricks Lakehouse Platform (Unified Analytics Platform)'s feature set?

No

Did Databricks Lakehouse Platform (Unified Analytics Platform) live up to sales and marketing promises?

Yes

Did implementation of Databricks Lakehouse Platform (Unified Analytics Platform) go as expected?

Yes

Would you buy Databricks Lakehouse Platform (Unified Analytics Platform) again?

Yes

Databricks Lakehouse platform is well suited for below use cases :
1. Process different types of data sources like structured data, semi structured data and unstructured data.
2. Process data different data sources like RDBMS, REST APIs, File servers, IoT sensors.
3. Provide support for Updates, Deletes, schema evaluation

Databricks Lakehouse platform is not well suited for below usecases :
1. Less data volume and doesn't have analytics requirements
2. Developers doesn't have skill set on spark and Hive