Databricks Data Intelligence Platform
Databricks, Inc.External reviews
640 reviews
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Good Vision, BI needs improvement
What do you like best about the product?
Data Processing is easier and all we need is in one place
What do you dislike about the product?
BI can do better so that we don’t need to take all the data to another platform and govern differently
What problems is the product solving and how is that benefiting you?
Data Digitization
It was fantastic got to meet many peers
What do you like best about the product?
I attended to explore how Databricks unifies data engineering, analytics, and AI. The platform’s integration with BI tools and support for Delta Lake worked well. Performance and collaboration features stood out. However, the learning curve and some UI complexities could be improved for newer users transitioning from traditional platforms.
What do you dislike about the product?
I attended the Databricks Data Intelligence Platform session but found it rather unremarkable. The features and performance were neither outstanding nor disappointing. It felt generic, with vague improvements and minimal innovation. Overall, I am uncertain about its distinct advantages, rendering my review neither particularly informative nor actionable for prospective users.
What problems is the product solving and how is that benefiting you?
1. Data Silos
• Brings data from multiple sources (structured, unstructured, streaming) into a unified platform for centralized access.
2. Slow Time to Insights
• Enables faster data processing with Spark, Delta Lake, and optimized workflows to accelerate decision-making.
3. Scalability Issues
• Handles growing data volumes and user loads efficiently with cloud-native, distributed compute.
• Brings data from multiple sources (structured, unstructured, streaming) into a unified platform for centralized access.
2. Slow Time to Insights
• Enables faster data processing with Spark, Delta Lake, and optimized workflows to accelerate decision-making.
3. Scalability Issues
• Handles growing data volumes and user loads efficiently with cloud-native, distributed compute.
Databricks Summit
What do you like best about the product?
Flexibility, scalability, extensible for the databricks
What do you dislike about the product?
Security aspects can be more flexible for financial firms
What problems is the product solving and how is that benefiting you?
Determining ratings for the company
Data Engineering Experience
What do you like best about the product?
The experience in developing workflows pipelines
What do you dislike about the product?
The platform is missong an access control, I mean you request access to a object and the flow in the platform
What problems is the product solving and how is that benefiting you?
The platform is solving all our problems
Databricks
What do you like best about the product?
Good experience in Data Analytics Industry. Products are relevant and cutting edge
What do you dislike about the product?
Some integration issues and transparency in cost
What problems is the product solving and how is that benefiting you?
Good experience in Data Analytics Industry. Products are relevant and cutting edge
Improvement on performance and foundation for our AI journey
What do you like best about the product?
Speed and performance, our daily sync jobs are running much faster compared to previous systems
What do you dislike about the product?
Support for legacy apps on on prem, needs more work to bring it to Databricks
What problems is the product solving and how is that benefiting you?
Solving the problem of long running jobs and performance, working towards bringing near realtime
Unified data Analytics
What do you like best about the product?
Integration to 3rd party solutions. Cost and adoption
What do you dislike about the product?
No integration to redshift on AWS. But works with snowflake
What problems is the product solving and how is that benefiting you?
Integration and unification
Databricks makes it easy to leverage their platform
What do you like best about the product?
Ease of use and feature set to perform analytics on a large dataset.
What do you dislike about the product?
Easy to rack up a big bill. Need to put additional measures for cost checks.
What problems is the product solving and how is that benefiting you?
Making it easier to get analytical work done fast.
Powerful unified data platform that transformed our analytics workflow
What do you like best about the product?
What I appreciate most about Databricks is its unified approach to data engineering and data science. The platform eliminates the traditional silos between our data engineers and data scientists by providing a collaborative workspace where both teams can work on the same datasets using their preferred tools - whether that's Spark, Python, R, or SQL. The Delta Lake technology has been particularly valuable for ensuring data quality and reliability in our pipelines. The auto-scaling clusters mean we don't have to worry about infrastructure management, and the notebook interface makes it easy to document and share our work. MLflow integration for experiment tracking and model deployment has streamlined our machine learning lifecycle significantly
What do you dislike about the product?
The main challenges we've encountered are around the learning curve and cost management. For team members coming from traditional SQL backgrounds, the transition to Spark-based analytics requires significant upskilling. The pricing model can be complex to predict, especially with auto-scaling clusters, and costs can escalate quickly if not monitored carefully. The UI, while functional, can feel overwhelming for new users with so many features and options. We've also experienced occasional performance inconsistencies during peak usage times, and some of the more advanced features require deep technical knowledge to implement effectively. Documentation, while comprehensive, can be dense and assumes a high level of technical expertise.
What problems is the product solving and how is that benefiting you?
Slow Time-to-Insight: Our analytics queries that previously took hours now complete in minutes, enabling faster business decision-making.
Data Infrastructure Complexity: We've eliminated the need to manage separate systems for data processing, storage, and ML, reducing operational overhead and technical debt.
Cross-Team Collaboration Barriers: Data engineers and data scientists now work in the same environment, improving project velocity and reducing miscommunication.
Scalability Bottlenecks: The platform automatically scales to handle peak workloads without manual intervention, supporting our growing business needs.
ML Model Governance: MLflow provides proper versioning, tracking, and deployment capabilities for our machine learning initiatives, ensuring models can be reliably moved to production.
These solutions have resulted in measurable business impact including reduced operational costs, faster product development cycles, and more data-driven decision making across the organisation.
Data Infrastructure Complexity: We've eliminated the need to manage separate systems for data processing, storage, and ML, reducing operational overhead and technical debt.
Cross-Team Collaboration Barriers: Data engineers and data scientists now work in the same environment, improving project velocity and reducing miscommunication.
Scalability Bottlenecks: The platform automatically scales to handle peak workloads without manual intervention, supporting our growing business needs.
ML Model Governance: MLflow provides proper versioning, tracking, and deployment capabilities for our machine learning initiatives, ensuring models can be reliably moved to production.
These solutions have resulted in measurable business impact including reduced operational costs, faster product development cycles, and more data-driven decision making across the organisation.
Best user
What do you like best about the product?
The distributed processing power is so quite good for all of data process in enterprise company
What do you dislike about the product?
It's quite hard to learn people who is not familiar with tech deeply
What problems is the product solving and how is that benefiting you?
There are ton's of data in enterprise company, databricks help us to process it by very easy way
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