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Databricks is great
What do you like best about the product?
I like the simple user interface that allows me to run spark without having to do much configuration. The Terraform support is also great.
What do you dislike about the product?
Databricks runtime is not available locally to run unit tests, so some workarounds have to be made for that.
What problems is the product solving and how is that benefiting you?
Running Spark jobs on big data.
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A lot easier to use than other tools I have used before.
What do you like best about the product?
Python notebooks that abstract away a lot of the complexity e.g. packages and infrastructure.
What do you dislike about the product?
The drop down menu/tool bar in the UI sometimes feels a bit clunky.
What problems is the product solving and how is that benefiting you?
Having multiple data pipelines that are able to be quickly developed and deployed, and then the output data sets made available to clients and internal teams
A great tool that simplifies your infrastructure
What do you like best about the product?
Opportunity to not manage Hadoop clusters.
What do you dislike about the product?
Cluster autoscaling doesn't always work as expected, and I would like to have more control over EC2 instances provisioning (availability to use multiple instance types in a single job/cluster, affinities, possibility to define some sort of topology, etc.). The whole experience is notebook focused.
What problems is the product solving and how is that benefiting you?
Enabling data-driven decisions by analyzing huge amounts of data
Great package for complete ML and Data engineering use cases
What do you like best about the product?
It's a complete package for development to deployment. Helps in experimentation and within a few clicks we can move it from experimentation to production.
What do you dislike about the product?
Sometimes lacks the feel of working on a traditional IDE kind of environment. However, it's not a significant drawback and one gets accustomed to it with time.
What problems is the product solving and how is that benefiting you?
Using a single platform for both data science and data engineering teams to work together and contribute. The complete journey from experimentation, modelling to deployment is seemless.
Delta Tables offers great scalable features with good performance, so low cost on cluster time.
What do you like best about the product?
Delta Tables, open source format, cloudFiles format, notebook UI and visualizations
What do you dislike about the product?
other companies do not use delta, so integration is not so simple, as delta sharing
What problems is the product solving and how is that benefiting you?
Big Data Extract Transform Load (ETL) process become very easy
Easy, fast and Reliable
What do you like best about the product?
Ease of access to multiple data sources and we can change the code to python to SQL,Scala etc it is impressive.
What do you dislike about the product?
Not able to create interactive visualization
What problems is the product solving and how is that benefiting you?
Major problem solving is of data warehousing with its multilayer data models
Excellent experience so far!!!!
What do you like best about the product?
We employ Python, Spark, and SQL to develop ELT pipelines, and Databricks is the most reliable and user-friendly option available. Developers may concentrate on writing code, creating pipelines, and creating models rather than spending time setting up the environment because it is very simple to do so.
What do you dislike about the product?
Knowledge of the cost model and recommendation engine to reduce burned DBUs There is an Overwatch notebook that offers general statistics about the environment, but it isn't developed enough and it also doesn't show you the cost of the infrastructure used in the back cloud kitchen. Platform as a whole is excellent.
What problems is the product solving and how is that benefiting you?
Two things to mention here.
- It unites all data teams from around the organization on one platform, reducing the need to maintain multiple copies of the same data.
- Because computation and storage are no longer linked, resizing any kind of warehouse environment is no longer necessary to boost compute capacity.
- It unites all data teams from around the organization on one platform, reducing the need to maintain multiple copies of the same data.
- Because computation and storage are no longer linked, resizing any kind of warehouse environment is no longer necessary to boost compute capacity.
Databricks is a very reliable way to run Spark
What do you like best about the product?
Databricks is the most reliable and flexible way to run Spark applications for data engineering workloads.
What do you dislike about the product?
Databricks is at the top end of the market on pricing.
What problems is the product solving and how is that benefiting you?
We use Databricks to run our Spark applications, which process hundreds of terabytes of data, need to be cost-effective, and run in a timely manner.
Works well in those grey areas of data management.
What do you like best about the product?
Easy to develop and maintain. Flexibility with transactional integrity.
What do you dislike about the product?
Can be more integrated with DW systems like Snowflake.
What problems is the product solving and how is that benefiting you?
Data Summary tables - I work with vast amounts of raw data. Being from the backend team, I do not need to ingest all of the data, but specific parts. Building summary tables by partly processing the data within the lakehouse framework is the most ideal solution I could find.
Hands down the most versatile and powerful data platform on the market
What do you like best about the product?
If you need to leverage python, spark, and SQL to build ELT pipelines, Databricks offers the most robust and easy-to-use solution for this. It doesn't require a lot of effort to configure and deploy, and allows developers to focus on building pipelines, instead of getting the infrastructure to work.
What do you dislike about the product?
I do wish there was more visibility into individual job cost, and overall cost as well- but this is a relatively minor complaint. Overall, the platform is great!
What problems is the product solving and how is that benefiting you?
I leverage Databricks for a variety of projects both for clients and personally. Anything involving large amounts of data, or streaming solutions and Databricks is my go-to.
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