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Best data all in one solution
What do you like best about the product?
Pyspark, Delta lake, The way that it integrates seamlessly with AWS services and how they managed to open source everything. It provides a great managed spark infrastructure.
What do you dislike about the product?
Harder to integrate with more legacy data sets. Requires you to move data into AWS to use.
What problems is the product solving and how is that benefiting you?
Databricks is creating a solution that allows us to query and manage our data lake with immense performance. Delta lake ensures ACID transactions on data and the query performance from databricks is unmatched
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A platform that connects the work Data Engineers, Data Analysts and Data Scientists all in one place
What do you like best about the product?
- Delta Lake & Lakehouse architecture for streaming and batch operations
- Databricks Academy provides hands-on learning and support
- Interact with Databricks resources via Terraform
- Databricks Academy provides hands-on learning and support
- Interact with Databricks resources via Terraform
What do you dislike about the product?
- Orchestration of pipelines could be improved. We currently use an external product to orchestrate our Databricks Spark jobs.
What problems is the product solving and how is that benefiting you?
- Enables data engineers to build reliable data pipelines and applications to manage their data.
- Supports ACID transactions
- New features are always being released & there is a strong Databricks community
- Supports ACID transactions
- New features are always being released & there is a strong Databricks community
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.
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
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.
Lakehouse is the best
What do you like best about the product?
Lakehouse combines the power of storage of data lake and reliability of warehouse, decoupled storage and compute is the best thing.
What do you dislike about the product?
Not enough resources earlier, but now we have all the required material in databricks academy.
What problems is the product solving and how is that benefiting you?
We are currently using redshift it is very hard to scale if we need extra compute, now we have decoupled compute we can spin up any end point according to our requirement
Databricks : Best Unified Platform for Data Engineering
What do you like best about the product?
Delta Table is the best. Spark in a very curated format
What do you dislike about the product?
Nothing as now . Its very good overallll
What problems is the product solving and how is that benefiting you?
We wanted to have a unified platform . The Partner connect is the very good feature of Databricks
Great product
What do you like best about the product?
Integarted UI for SQL , Spark , Python . This makes the job really seamless
What do you dislike about the product?
Nothing as of now . Enjoying the product
What problems is the product solving and how is that benefiting you?
We can leverage the concept of delta lake for our use cases
It's really useful for big datasets
What do you like best about the product?
Lesser Running time, handling big datsets, user-friendly platform
What do you dislike about the product?
Cluster active time is less, active time should be increased when not in use
What problems is the product solving and how is that benefiting you?
Helps in Data Warehousing on big datasets, building data engineering pipeline and ML models end to end
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