It's mainly used for data science, data analytics, visualization, and industrial analytics.
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
756 reviews
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External reviews are not included in the AWS star rating for the product.
Processes large data for data science and data analytics purposes
What is our primary use case?
What is most valuable?
Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours.
So that's why it's quite convenient to use for data science, for training machine learning models. By using more computing power, you can make it even faster.
What needs improvement?
There is room for improvement in visualization.
For how long have I used the solution?
I used it for two years. I worked with the latest update.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten. I didn't face performance drops.
What do I think about the scalability of the solution?
I would rate the scalability an eight out of ten.
How are customer service and support?
Databrick's support is great. If we need any support, they are very quick with it. And they genuinely want you to use Databricks. So, whatever we ask them, they come up with multiple solutions to problem statements. That's really good.
Overall, the customer service and support are very good.
Which solution did I use previously and why did I switch?
I personally prefer using Databricks. However, we also considered using Snowflake, but the pricing was different. It's price per query.
So, as per your storage, a data scientist or a data analytics team needs to query again and again, which does not suit a data-heavy organization.
What was our ROI?
It's a good return on investment for Databricks from a delivery perspective. Delivered multiple dashboards. So, it's quite a good return on investment. And being a small organization, everyone can use Databricks, and cost-wise, it's also good for small organizations.
Which other solutions did I evaluate?
If the company is a startup, Databricks might be suitable. If a big company needs a lot of storage, Teradata might be best for them. It depends on the situation.
What other advice do I have?
Overall, I would rate the solution a eight out of ten. I would definitely recommend this solution for small organizations.
Data + AI should be unified
What do you like best about the product?
Before exploring Databricks I had worked on many tools & their integration to make Data flow simpler but Databricks is doing wonders in this space by unifying Data + AI at one platform & also giving smooth UI to Intereatc & get your job done in a simplified manner
What do you dislike about the product?
Although my experience is really good but what I have observed is that data bricks is doing wonders with Azure most of the time, I think they introduce Databricks as PAAS with other platforms like AWS especially.
What problems is the product solving and how is that benefiting you?
I think overall the Platform is really good but I loved their Data Governance support using Catalog is really a solution to most of the Data Governance problems.
The best lakehouse on the market
What do you like best about the product?
- SQL warehouse,
- MLflow,
- Delta,
- Ecosystem
- MLflow,
- Delta,
- Ecosystem
What do you dislike about the product?
- Dashboards could be improved to match BI product's capabilities
What problems is the product solving and how is that benefiting you?
Data engineering and machine learning
An easy to setup tool that provides its users with an insight into the metadata of the data they process
What is our primary use case?
My company uses Databricks to process real-time and batch data with its streaming analytics part. We use Databricks' Unified Data Analytics Platform, for which we have Azure as a solution to bring the unified architecture on top of that to handle the streaming load for our platform.
What is most valuable?
The most valuable feature of the solution stems from the fact that it is quite fast, especially regarding features like its computation and atomicity parts of reading data on any solution. We have a storage account, and we can read the data on the go and use that since we now have the unity catalog in Databricks, which is quite good for giving you an insight into the metadata of the data you're going to process. There are a lot of things that are quite nice with Databricks.
What needs improvement?
Scalability is an area with certain shortcomings. The solution's scalability needs improvement.
For how long have I used the solution?
I have been using Databricks for a few years. I use the solution's latest version. Though currently my company is a user of the solution, we are planning to enter into a partnership with Databricks.
What do I think about the stability of the solution?
It is a stable solution. Stability-wise, I rate the solution an eight to nine out of ten.
What do I think about the scalability of the solution?
It is a scalable solution. Scalability-wise, I rate the solution an eight to nine out of ten.
My company has a team of 50 to 60 people who use the solution.
How are customer service and support?
Sometimes, my company does need support from the technical team of Databricks. The technical team of Databricks has been good and helpful. I rate the technical support an eight out of ten.
How was the initial setup?
The initial setup phase of Databricks was good. You can spin up clusters and integrate those with DevOps as well. Databricks it's quite nice owing to its user-friendly UI, DPP, and workspaces.
The solution is deployed on the cloud.
The time taken for the deployment depends on the workload.
What's my experience with pricing, setup cost, and licensing?
I cannot judge whether the product is expensive or cheap since I am unaware of the prices of the other products, which are competitors of Databricks. The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts.
What other advice do I have?
It is a state-of-the-art product revolutionizing data analytics and machine learning workspaces. Databricks are a complete solution when it comes to working with data.
I rate the overall product an eight out of ten.
Embracing the Future : A Deep Dive into Databricks Lakehouse Platform
What do you like best about the product?
1. Advanced Analyrics and AI : Beyond traditional data management , Databricks Lakehouse platform offera a comprehesive suite of tools for advanced analytics and artificak Intelligence,
2. Data Quality and Goverance.
2. Data Quality and Goverance.
What do you dislike about the product?
Databrikcs platform offer numerous benefits and innovative features, but few aspects might find less favorable like
1. Complexity of New Users
2. Cost Considerations.
3.Limited Flexibility
1. Complexity of New Users
2. Cost Considerations.
3.Limited Flexibility
What problems is the product solving and how is that benefiting you?
Databricks Lakehouse platform aims to address several challenges that organizations face in the realm of data management , analystics and decision making.
1. Unified Data Platform
2.Advanced Analytics and AI
1. Unified Data Platform
2.Advanced Analytics and AI
Driving AI and Data Innovation with a Unified Databricks Platform
What do you like best about the product?
I use Databricks for ETL, Reporting, and AI, and I appreciate that it works as one unified solution for all data and AI needs. It makes it easier to track data and create insights, helping us deal with data silos. I like the Unity Catalog as it helps us manage and govern data in one place. I also like using AgentBricks as a multi-agent system for creating AI applications from PDFs and other documents. I find Genie valuable as it allows business users to ask questions in natural language and get exact answers. The initial setup of Databricks was very easy, making the transition smooth.
What do you dislike about the product?
I think workflow could be improved by adding multiple triggers to the same pipeline, as for now, if we want to schedule the same pipeline multiple times in a day, we have to clone it for each time.
What problems is the product solving and how is that benefiting you?
I use Databricks to eliminate data silos and make data tracking and insights creation easy. Unity Catalog manages data governance, AgentBricks develops AI applications, and Genie provides answers using natural language on structured data.
Most advanced data platform
What do you like best about the product?
Databricks has been developing an excellent product with new features being added constantly. ETL/ELT, dbt integration, integration with external sources, and many more features make it a product that is versatile and highly effective. Managment of permissions is also extremely easy.
What do you dislike about the product?
Some automated recommendations on optimizing jobs are lacking, so you could end up spending quite a lot of money without the best performance. The platform is also not for small scale use-cases.
What problems is the product solving and how is that benefiting you?
Databricks is providing the fundamental building block of our data warehouse + data lake + data processing platform from which other systems receive analytics data.
Unified Still Federated Lakehouse Platform
What do you like best about the product?
A great platform to focus on industry challenges around data and ai. Good part is solutions for those challenges are quickly built, tested and released. Participation during private preview also make sure that these solutions are fit for purpose to industry challenges.
Best features floats around combining data lake and datawarehouse capability to help reduce cost and deliver faster with improved security
Best features floats around combining data lake and datawarehouse capability to help reduce cost and deliver faster with improved security
What do you dislike about the product?
Its integration with native cloud services is still weak, out of the box integration & use with org identify federation is still not mature. Along with capability to integrate with enterprise catalog and buillding a unified metric system for organization.
What problems is the product solving and how is that benefiting you?
Unified view for all our data sources, easy sharing of data with our product team, easy platform for data owners to democratise their data. and central place to apply security and governance.
It is a one stop solution to collaborate for all Data Engineering and Data Science activities
What do you like best about the product?
Collaboration,Feature store,MLOps,scheduling
What do you dislike about the product?
Don't have a way to put dependencies between workflows
What problems is the product solving and how is that benefiting you?
It has helped me build the datalake for business intelligence usecases
One of the best cloud data warehousing solution
What do you like best about the product?
Databricks Lakehouse Platform impressively unifies data lakes and data warehouses, empowering seamless data access and analysis. Its Apache Spark-powered engine ensures lightning-fast processing, while advanced analytics and machine learning capabilities drive data-driven insights. With robust security, auto-scaling, and managed services, Databricks simplifies data management and boosts collaboration among data teams. An extensive range of integrations further enhances its versatility, making it a game-changer for data-driven organizations.
What do you dislike about the product?
Learning curve - for users unfamiliar with Apache Spark there may be a learning curve to fully utilize platform capabilities.
Complexity - managing and optimizing large-scale data workflows can be comples, requiring skilled data engineers and administrators,
Sometimes new features are not fully tested, which may cause some problems in the future - but honestly it's not a big disadvantage.
Complexity - managing and optimizing large-scale data workflows can be comples, requiring skilled data engineers and administrators,
Sometimes new features are not fully tested, which may cause some problems in the future - but honestly it's not a big disadvantage.
What problems is the product solving and how is that benefiting you?
Keeping everything as all in one product for creating ETL pipelines and data governance solutions. Also it lets you simply scale your workload if it's really needed.
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