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Build fast and reliable data pipelines batch/streaming supporting unstructured and structured data
What do you like best about the product?
Data Governance and Simplified Schema.
Support for unstructured along with structured data enabling support for any use cases to build machine learning, business intelligence, and streaming features. Also support Streaming Live Tables which is a new feature in latest version.
Support for unstructured along with structured data enabling support for any use cases to build machine learning, business intelligence, and streaming features. Also support Streaming Live Tables which is a new feature in latest version.
What do you dislike about the product?
performance benchmark needs to be verified with other competitors like Snowflake. Looks like(as per the documentation) the latest version is blazing fast.
What problems is the product solving and how is that benefiting you?
Unstructured and Structured data in a unified repository to build Machine Learning and BI capabilities.
Recommendations to others considering the product:
How simple to deliver BigData applications. Hassle-free administration and maintenance.
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The Future of Data is Databricks Lakehouse!
What do you like best about the product?
Databricks support services needs a special nod, they have come to the table day in and day out with solutions and ideas to better our enterprise environment for any channel we were working with. Also, the support within the platform multi-format data, github support, and an open-source experience are what I love best about the platform.
What do you dislike about the product?
I'd like a better more seamless way to integrate development teams into our environment. This does feel a bit challenging at times with some minor re-work, but I think there could be progress made in this area. Particularly speaking to how you manage workloads for teams with multiple workspaces.
What problems is the product solving and how is that benefiting you?
It's solving many problems but mostly eliminating siloed development environments and centralization of code as a service for global development and product creation. We have in the past had many areas of sources of truth in data and now we are building a more streamlined ecosystem of data services with a centralized solution of truth for Data Opreations.
Data bricks review
What do you like best about the product?
Data bricks Lake House architecture seems promising
What do you dislike about the product?
I don't see much video tutorials. If we have tutorials for free we can learn more
What problems is the product solving and how is that benefiting you?
We are building etl platform where we use data bricks
I love the intuitive user interface.
What do you like best about the product?
Easy to use for a SQL only technical person.
What do you dislike about the product?
I would like SQL query designer to make the text
What problems is the product solving and how is that benefiting you?
Geocoding data natively with Precisely's Geocoding SDK.
Recommendations to others considering the product:
The Lakehouse is an easy to use platform.
Free yourself from the DataWarehouse
What do you like best about the product?
Your data is not trapped with a propietary tool or platform.
You can access your data thru an SQL interface or interface it with Python, Scala or R API.
Much faster than other DWs.
You can access your data thru an SQL interface or interface it with Python, Scala or R API.
Much faster than other DWs.
What do you dislike about the product?
The notebook editor could be better for copying and pasting.
Also it needs better Find lookup function for really long cells.
The new feature identity column feature for tables, needs better support to Create or Alter a table from pyschark commands.
Also it needs better Find lookup function for really long cells.
The new feature identity column feature for tables, needs better support to Create or Alter a table from pyschark commands.
What problems is the product solving and how is that benefiting you?
One central repository single point of truth for all your data lake, and lakehouse governance across companies, customers, departments etc.
One real single point of truth!
One real single point of truth!
Recommendations to others considering the product:
look no further switch
The Databricks Lakehouse Platform provides a seamless experience for the user community.
What do you like best about the product?
The platform integrates the best of the warehouse and lake.
What do you dislike about the product?
As of now, there is nothing to report on disadvantages.
What problems is the product solving and how is that benefiting you?
Being on the Azure stack allows for a seamless integration across the platform of databricks to Power BI.
Easiest way to onboard to spark and other advanced analytics
What do you like best about the product?
I love that Databricks abstracts away all of the administrative overhead of running spark clusters.
What do you dislike about the product?
I wish that spark could do run time partition elimination
What problems is the product solving and how is that benefiting you?
1. data mobility 2. data latency 3. workload isolation
LakeHouse Why
What do you like best about the product?
workload isolation is the best feature for our use case.
What do you dislike about the product?
serverless endpoint with AAD passthrough has few selections
What problems is the product solving and how is that benefiting you?
Delta Live tables are solving the ETL at runtime problem
Recommendations to others considering the product:
Just Do It!
Great platform for rapid delivery of data products
What do you like best about the product?
Single pane of glass to create an end to end solution
What do you dislike about the product?
No dislikes yet, some aspects of capability delivery are difficult to govern
What problems is the product solving and how is that benefiting you?
Centralizing management of data
Versatile, scalable, and adaptable framework for building a modern analytics stack
What do you like best about the product?
Databricks Lakehouse brings together BI, SQL-based data warehouses, data governance, processing and DAG creation, and ML (and more) under one umbrella. Competitors like Dataiku, Snowflake, Cloudera, etc. really can't compete and don't bring the same value proposition out of the box.
What do you dislike about the product?
Unless you're willing to keep your clusters that serve DB SQL queries spun up at all times, the "first query wait" can be quite annoying. However, using Databricks in its serverless form (managed environments) would mitigate that drawback.
What problems is the product solving and how is that benefiting you?
Streamlining data stacks and reducing the cost and complexity of deploying analytics workloads. Databricks has matured and been extended dramatically over the past few years, almost always for the good.
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