Databricks Data Intelligence Platform Reviews & Product Details - Page 2

What do you like best about Databricks Data Intelligence Platform?

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 Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

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. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

Databricks data intelligence platform is very unique and interesting product, it is very efficient and makes running programs so much faster and easier. Over the cost-efficient price and the uses of this platform bring so appealing is what made me choose this product. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

Someone I disliked about Databricks Data Intelligence Platform is it is a big slow at times when multiple users are using it which could be worked on. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

Honestly, it’s how it turns the chaos of raw data into something beautifully orchestrated—like jazz, but with less saxophone and more Spark.

I love that it’s not just a tool—it’s an entire ecosystem. It brings data engineering, analytics, and AI into one unified environment. That means I don’t have to duct tape a dozen tools together just to move a pipeline forward. Fewer silos, more flow. And the fact that it’s built on open standards like Delta Lake and Apache Spark? Chef’s kiss.

The collaborative features are also huge. Being able to work seamlessly across teams in notebooks, share insights, and iterate in real time? It’s like Google Docs for data nerds, but smarter and with fewer formatting headaches.

Oh, and Unity Catalog? Game-changer. It gives me visibility and governance without making me feel like I need a second job in security.

So yeah—what I like most is that it makes doing complex things feel, well… less complex. It’s not just about managing data—it’s about getting real intelligence out of it, fast. And that’s exactly the kind of velocity I like. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

First off, pricing transparency can be… let’s call it “mysterious.” You think you’re just running a simple job, and then BAM—surprise costs like it’s your birthday, but the gifts are all invoices. I’d love a bit more clarity and control there, especially when you’re trying to scale responsibly. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

This lake house architecture brings the best of both data lakes and warehouses , so we don't have to deal with the unnecessary complexity. Delta lakes ensures reliability while the notebook based interface makes collaboration seamless. The platform ability to handle batch, streaming, and machine learning workloads in one place is a huge advantage. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

The pricing can get expensive, especially if workloads aren't optimized properly, also while the notebooks are great they could use better version control for collaborative work . the initial learning curve can be a bit steep for those new to spark but once you get the hang of it. It is powerful tool Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

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. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

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. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

What I like best as a Data Architect is the possibility to manage your data starting from the ingestion to the serving endpoints everything is managed and monitored in the same platform creating reusable resources optimizing costs and efforts while conserving full flexibility. All of that seasoned with open source mindset. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

I think the lakeflow connector are still in embryonic stage, I think it will get better with time but at the moment is not the best on the market Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

Databricks is a tool that is constantly evolving. I really appreciate the number of features they release, and the fact that they are up to date. It's an everyday platform that adapts to all use cases and is easy to integrate. It's an all-in-one solution with ETL with warehouses, Python, Spark, Scala, machine learning, and GenAI. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

Sometimes I wish they would update the documentation more, that there weren't so many changes in the API .

The release notes of the changes were better explained to us and that we would have time to address the changes.

Customer support is one thing that they have to improve too Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

What I really like about Databricks is how it brings every technical requirements under one space like kind one stop place for anything related to data. From cleaning and organizing to building machine learning models, it makes the whole process less messy. We could work as a team without constantly emailing or switching tools. Performance wise, it holds up even when we throw big workloads at it, and it connects well with other tools we use. Real-time data processing is smooth, and I’ve noticed we get insights much faster now. It’s also got solid controls around data access and tracking, which gives peace of mind on the security side. Overall, it's a smart, efficient platform that makes working with data feel way more natural. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

Databricks offers a good environment for data processing and analytics, but it does come with its set of challenges. One of the primary challenge is the learning curve, especially for those new to big data tools.But customer support really try their best. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

Quality of Databricks services are top notch and best also their support team always reply fast and with resolution for any techy questions. I like to use Databricks for my data analytical work. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

Easy to use infrastructure and number of integration make them very useful and reliable platform for us to manage or datasets and ML related works. Review collected by and hosted on G2.com.

What do you like best about Databricks Data Intelligence Platform?

Predictive model for early hospital readmission risk detection was developed by our firm. We were processing sensitive health records using Databricks because security and compliance were our top priorities. Databricks support for HIPAA compliance and secure workspace management made it a trustworthy platform to host patient datasets. Using Delta Lake we handed the millions of records with the reliable performance. The integration with pandas and MLflow within notebook was also seamless. I especially appreciate the real time dashboard we build for a hospital admin staff to view live model prediction and alerts. Review collected by and hosted on G2.com.

What do you dislike about Databricks Data Intelligence Platform?

During this project one of the biggest challenge we faced was setting up real time data streaming with HL7 format via Kafka into Databricks. While Databricks does support auto loaders but we had to write a fair amount of custom logic to parse and validate complex healthcare specific schemas Review collected by and hosted on G2.com.