Databricks Data Intelligence Platform

What do you like best about the product?

It’s very intuitive. The AI genie feature is also really helpful for non-technical folks when they need to write SQL queries. Excellent value!

What do you dislike about the product?

It is well integrated with multiple platforms. For example, for us, we transform our data from Hubstaff Timer and are able to generate from our different layers, from silver to gold. The charts are very, very performative as well. Great integration as well as performance

What problems is the product solving and how is that benefiting you?

Solving the real-time data as well as metrics for our campaigns, it's able to process on a nightly basis, which is very helpful.

What do you like best about the product?

I use Databricks to transform and analyze large volumes of data, and it allows me to unify data from various SQL functions to cloud storage systems, which makes analysis easier. I find eliminating information silos vital for team collaboration and appreciate the optimized Spark engine for its performance with large volumes of data. I appreciate its compatibility with languages like Python, Scala, and SQL, making it comfortable for every team member to work with Databricks. It fosters smoother communication and allows for making immediate adjustments, which is something I value. Additionally, I like how it facilitates collaboration between different teams.

What do you dislike about the product?

I would appreciate specific training resources to help me become familiar with the advanced features. Also, I found the initial setup to be a little difficult.

What problems is the product solving and how is that benefiting you?

I use Databricks to manage and unify data from various sources, making analysis easier. It solves the problem of eliminating information silos and processing large data volumes, enhancing team collaboration with its optimized Spark engine.

What do you like best about the product?

as a data engineer we use Databricks Daily. we integrate databricks in to other cloud. we get the data and process the TB's of the data. and Genie code and the inline Assistant were the most helpful tools for me on my project. and it is user friendly interface

What do you dislike about the product?

Cost control is another drawback. It is undoubtedly strong, but expenses might quickly increase if you are careless with cluster usage or auto-scaling settings. To keep everything under control, you need to exercise some self-control and keep an eye on things.

What problems is the product solving and how is that benefiting you?

It helps me integrate with other cloud platforms and process TBs of data.

What do you like best about the product?

I like the community. The people that use Databricks are pretty cool people, and I also like how they are a champion for the open source. Having a nice community of technologists to lean on and talk to opens my eyes to the possibilities on the platform. I love being able to do things for free slash cheap, and I also like being able to bring my own tooling and libraries to my projects. Exploring different tooling and libraries that people tell me about is great, and the fact that I can just pull anything I really want from GitHub so simply on Databricks is a huge value add because I can go on to any project and make some magic happen.

What do you dislike about the product?

I think the developer experience in Databricks could be improved. You kind of have to choose between developing in the UI or developing locally, and it's a little bit clunky in my opinion. There are pros and cons to both, so I'd like to see those differences between local development and UI development removed. Also, the initial setup was pretty tough, which wasn't entirely Databricks' fault, but dealing with the high-level security and firewall software of our client added challenges. The Databricks team was helpful in overcoming these hurdles, though.

What problems is the product solving and how is that benefiting you?

I use Databricks to create ETL pipelines, helping my company solve net revenue calculation issues by integrating data from source systems to dashboards. It aids informed decision-making for stakeholders.

What do you like best about the product?

I love using Databricks for bringing all our data together and making sure everything is more organized without isolated areas. The collaborative notebooks are fantastic because they allow me to work on code simultaneously with colleagues, which greatly speeds up the workflow. I also appreciate the Spark integration as it removes the hassle of manually configuring clusters. Databricks saves a lot of time due to the speed at which it processes data. The fact that it's cloud-based made the initial setup easy, which is another plus.

What do you dislike about the product?

Being a bit demanding, I would like them to improve the learning curve, because for someone just starting out it can be a little overwhelming due to the large number of configuration options, permissions, and governance settings.

What problems is the product solving and how is that benefiting you?

Databricks organizes our data, eliminating isolated areas for team collaboration. I love the collaborative notebooks and Spark integration for speedy workflows. It saves us time with quick data processing.

What do you like best about the product?

Anyone can adapt and learn and execute it!

What do you dislike about the product?

There are frequent changing naming convention

What problems is the product solving and how is that benefiting you?

AI automation and agentic releated problems

What do you like best about the product?

I use Databricks as the backbone for all my data and AI work. I love that everything is in a single place and all connects, which allows me to manage everything from raw data digestion to deploying AI products. Unity Catalog provides a single governance source of truth with permissions throughout the platform, which is incredibly useful. Genie Spaces offer an interface in natural language for non-technical stakeholders, saving me time as I don't need to create additional Tableau reports. I can ship everything as code rather than clicking through notebooks manually, which lets me scale much faster. Databricks is a comprehensive platform and is ahead of the curve when it comes to artificial intelligence.

What do you dislike about the product?

The biggest issue I have is that I'm not applied for admin so I don't have visibility into a lot of my costs or access to control more things in the platform. I also wish there was a way in Genie code to make it more clear which aspects are within my control and which are not, and to have an integrated system to notify my platform admin when there are issues.

What problems is the product solving and how is that benefiting you?

I use Databricks as the backbone for all my data and AI work. It's an all-in-one platform, eliminating the need for handoffs between different tools. Unity Catalog gives me a single governance source, ensuring consistency and saving my time.

What do you like best about the product?

Amazing platform to run AI on a massive scale without complexity

What do you dislike about the product?

The pricing can be challenging if you don't have enough knowledge

What problems is the product solving and how is that benefiting you?

It’s one of the best ways to run AI and ETL on large amounts of data. Databricks also comes with industry-ready features that make it easier to work at scale.

What do you like best about the product?

I like how Databricks merges our warehousing and lakes into one architecture, eliminating the need to maintain separate storage and compute for operational reporting and predictive work on sensor data. This unified source of truth helps keep data duplication and sprawl in check while focusing on the operational picture. The Lakehouse concept of bringing warehousing and lake environments under one roof won me over. Unity Catalog simplifies governance by providing a clear view of data access, and Delta Live Tables efficiently manages our telemetry pipelines, reducing the effort needed for ensuring their reliability. I also find the initial setup quite easy with no bigger issues encountered.

What do you dislike about the product?

My one reservation is the cost side. The DBU model can climb quickly, and if cluster policies and auto-scaling limits go unattended, spend has a way of getting ahead of you. We saw this play out during an early stretch of heavy streaming, which pushed us to tighten our boundaries and keep a firm hand on utilization. Budget discipline rewards constant attention rather than a set-and-forget approach. I'd want clearer, real-time visibility into DBU spend at the cluster and workload level, with configurable alerts that flag when a job or fleet's consumption starts trending past its expected envelope before the bill lands, so budget governance becomes proactive rather than a monthly reconciliation exercise.

What problems is the product solving and how is that benefiting you?

Databricks ends siloization by merging warehousing and lakes, so I manage data from one governed source of truth. It allows me to scale telemetry across client fleets and focus on operations without reconciling parallel systems.

What do you like best about the product?

I really appreciate that Databricks doesn't force a trade-off between control and convenience. My developers can access the cluster configuration for detailed tuning when necessary, but for routine tasks, the managed notebooks, job scheduling, and Unity Catalog take care of everything without needing a platform specialist. I like that Databricks borrows from software engineering practices instead of sticking to the classic analytics silo. The integration with version control, CI-friendly job definitions, and separated environments mean our data work follows the same review and release processes as the rest of our codebase. This consistency makes it easier to manage as the team grows.

What do you dislike about the product?

I find the on-ramp steeper than it should be for people who aren't already fluent in the ecosystem. When someone on my team picks it up for the first time, there's a long stretch where they're productive with the UI but not with what's happening underneath. Spark is the main pain point. When a job degrades or fails, the reasons are rarely obvious, and tracing a problem back to a skewed join or a bad shuffle usually eats far more of a senior developer's attention than it deserves. Richer query plan visualization, with plain-language explanations of why the optimizer made a given choice, would remove a lot of that guesswork and stop these investigations from landing on the same two or three people every time.

What problems is the product solving and how is that benefiting you?

Databricks provides a governed data repository, making pipeline changes reviewable in pull requests. I can plan data work in sprints alongside engineering tasks, eliminating separation between data and software development.