Databricks Data Intelligence Platform
Databricks, Inc.External reviews
637 reviews
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External reviews are not included in the AWS star rating for the product.
Why Databricks Data Intelligence Platform?
What do you like best about the product?
Databricks simplifies big data processing with AI-powered analytics, seamless integration, and collaborative workspaces, making data-driven decisions faster and more efficient. Implementation is smooth, and customer support is helpful.
What do you dislike about the product?
Databricks is great, but the cost can escalate quickly, especially with high workloads and auto-scaling.
What problems is the product solving and how is that benefiting you?
Databricks makes working with data easier by combining analytics, AI, and storage in one place. It helps teams work faster, automate tasks, and get insights quickly—saving time and effort.
Easy to use, easy to access support system, unified lakehouse architecture and timely new features.
What do you like best about the product?
Flexibility of using languages like Python, Pyspark and SQL. New file arriving feature. variety of options to connect with almost all kind of source. Very simple implementation of unity catalog which was hard to manage initially. Volumn that works seamless with python/pandas code.
What do you dislike about the product?
Databricks diagnose error suggestion. Failed to provide queries for like mail attachment extraction, AES 256 encrypt code etc. Very good for support in python, pyspark and SQL code but not in rare usecase like mentioned above.
What problems is the product solving and how is that benefiting you?
Complex logic and Expensive processing, Unified batch and stream processing, data governance by unity catalog, use of separate BI tool etc.
Databricks Analytics Amazing Tool
What do you like best about the product?
It provide codes based on taking context from previous cells, which helps in developing code better.
Serverless querying is faster and cheaper, which helps build and query effectively.
Serverless querying is faster and cheaper, which helps build and query effectively.
What do you dislike about the product?
Nothing disappointing about this product.
What problems is the product solving and how is that benefiting you?
Helps ingest data from various sources and structure data properly. Unity catalogue also helps in data governance as similar data under a single catalogue.
It helps create jobs and utilities based on custom requirement.
It helps create jobs and utilities based on custom requirement.
Unified Data Analytics Platform
What do you like best about the product?
There are so many features which I loved and some of them are unity catalog (data governance), Serverless compute (sql warehouse) and delta acid transactions (time travel in case of accidental data delete or update)
What do you dislike about the product?
there is nothing to say but in previously when databricks changed the UI design then little bit problem occured but now I am used to
What problems is the product solving and how is that benefiting you?
Its real streaming helps lot as we receive the data in near to real time and its provides all the supporting features apart from this easy to make different kind of ETL and data integration from various source
Databricks is a great solution for data engineering and analytics
What do you like best about the product?
I love Databricks because it consolidates data engineering, machine learning and analytics into one and the feat of using collaborative notebooks also enables real-time and seamless teamwork in working between a data engineer working on data pipelines and a data scientist running various experiments. And it handles large-scale data quite easily and running complex SQL queries within seconds with no infrastructure related issues. Also it has some built-in governance tools like unity catalog which help me in managing data lineage and controlling access.
What do you dislike about the product?
Databricks can be quite overwhelming for beginners especially if they do not have a good grasp of sql and spark to begin with. And the pace of their updates, although is quite good, it tends to introduce breaking changes which can be a pain to keep up with. Also the pricing can get expensive at scale especially for teams that work with really big sets of data.
What problems is the product solving and how is that benefiting you?
Before Databricks, we had disjointed processes, terribly slow data processing and no easy way to collaborate but now, we can integrate multiple data sources more easily and process big data in an efficient manner. Also this rapid development of machine learning models makes the infrastructure manageable for us and we save hundreds of hours with automation – not just in maintaining infrastructure but in thinking innovation first.
A Game-Changer for Data and AI Teams
What do you like best about the product?
the most helpful feature is unity catalog (data governance) and sql warehouse
What do you dislike about the product?
now a days nothing, it is already too enhanced
What problems is the product solving and how is that benefiting you?
Data Integration from various sources like mongoDB, Postgres, ADLS, SFTP, SQL server, big query and etc as we get the data from mentioned sources and need to store in multiple data layer (raw data, flatten date, aggregated data) according to business, so its help in segregation based on catalog according to line of business use case.
And ETL (databricks workflow) provides lots of option for scheduling jobs in multiple way as per requirement.
And ETL (databricks workflow) provides lots of option for scheduling jobs in multiple way as per requirement.
Perfect tool for Big data workflows and great for collaborative Data science
What do you like best about the product?
Its ability to scale effortlessly across cloud environments and handle big data pipelines with ease and the collaborative workspace
What do you dislike about the product?
Issue while using Assistant which makes high memory usage, Occasional issues with cluster start-up times and delays in job execution, Limits in serverless computes etc.,
What problems is the product solving and how is that benefiting you?
Major problem like if we go for AWS data engineering everything is not much coupled and this problem has been resolved by databricks because of unified env
Best unified platform for AI and data analytics
What do you like best about the product?
It stands out as it seamlessly integrates data engineering, analytics and AI/ML workloads. Their Lakehouse architecture is a game changer as it combines the best of data lakes and warehouse, eliminating then need for complex ETL pipelines.
What do you dislike about the product?
Cluster startup is slow and time consuming. Price of products are very high if it is not used to its fully utilizing capabilities.
What problems is the product solving and how is that benefiting you?
We use for big data processing and real time analytics and AI driven insights. It has significantly improved data governance, performance and collaboration across teams. By replacing our legacy ETL workflow we have reduced processing time by half and improved model deployment efficiency.
The Tool for data analysis is Phenomenal
What do you like best about the product?
It offers interactive notebooks where different users can collaborate on data projects in real time.
What do you dislike about the product?
The disadvantage is that depending on the cluster, it takes a long time to pull the database.
What problems is the product solving and how is that benefiting you?
Help to process large volumes of data, understand and optimize problems, because through analysis we can make more assertive decisions.
Databricks -Data transformation and pipeline Use
What do you like best about the product?
Databricks is very user friendly platform whuch supports multiple database and scripting languages at same place.
Pyspark and delta feature enhance the speed of data extraction
AI assostant auto complete the code and optimize when needed to do that.
Lots of paid connectors are available to use.
Pyspark and delta feature enhance the speed of data extraction
AI assostant auto complete the code and optimize when needed to do that.
Lots of paid connectors are available to use.
What do you dislike about the product?
Transformation from sql to pandas can be very time consuming.
Estimated runtime should be available so use can optimize the pipeline or notebook.
Estimated runtime should be available so use can optimize the pipeline or notebook.
What problems is the product solving and how is that benefiting you?
Simple platform to transform or aggrefate the data to create business data views/table.
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