Databricks Data Intelligence Platform
Databricks, Inc.External reviews
637 reviews
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Best Data Engineering, ML, Data Science & analytics lakehouse platform
What do you like best about the product?
Autoloader
Change Data Feed
DLT pipelines
Schema evolution
Jobs Multitask
Integration with leading Git Providers, Data Governance and security tools
MLflow AutoML
Serverless SQL endpoints for analyst
Photon accelerated engine
Change Data Feed
DLT pipelines
Schema evolution
Jobs Multitask
Integration with leading Git Providers, Data Governance and security tools
MLflow AutoML
Serverless SQL endpoints for analyst
Photon accelerated engine
What do you dislike about the product?
No GUI-based drag & drop
Complete Data Lineage visualization at the metadata level is still no there
NO serverless Cluster for data engineering pipelines if you use existing interactive clusters, only available through job clusters through DLT
Every feature has some limitations involved
More work is needed on orchestration workflows
Complete Data Lineage visualization at the metadata level is still no there
NO serverless Cluster for data engineering pipelines if you use existing interactive clusters, only available through job clusters through DLT
Every feature has some limitations involved
More work is needed on orchestration workflows
What problems is the product solving and how is that benefiting you?
Unified Batch & streaming pipeline
Delta Lake
Versioning & History
ACID transaction through delta log
Data curation through Validation & quarantine
Data Ingestion through Autoloader
Delta Lake
Versioning & History
ACID transaction through delta log
Data curation through Validation & quarantine
Data Ingestion through Autoloader
Databricks - Best Unified Delta Lakehouse Platform in Data & AI Analytics space
What do you like best about the product?
Unified Batch & Streaming for source systems data
Autoloader capability, along with Schema Evolution
Delta Live Table & orchestrating with Pipelines
CDC Event streams for SCD1 & SCD2 using DELTA apply changes
Databricks Workflows - Multi-task jobs
Serverless SQL Photon cluster along with Re-dash integrated Visualization
Unity Catalog
Delta Sharing & Data MarketPlace
Data Quality expectations
Integration with Collibra, Privacera & other security & governance tools
Autoloader capability, along with Schema Evolution
Delta Live Table & orchestrating with Pipelines
CDC Event streams for SCD1 & SCD2 using DELTA apply changes
Databricks Workflows - Multi-task jobs
Serverless SQL Photon cluster along with Re-dash integrated Visualization
Unity Catalog
Delta Sharing & Data MarketPlace
Data Quality expectations
Integration with Collibra, Privacera & other security & governance tools
What do you dislike about the product?
Issue in running multiple streaming jobs in same cluster
Job clusters can't be reused even for the same retry in PRODUCTION, since shutdown immediately after the job run/fail is set by default - Need to check any options to increase this limit
Multi-Task jobs requires TASK output should be passed to next input TASK and also need to support FAIL on trigger and setting OR dependent predecessors to trigger ,Currently supports only AND
No serverless option for Data engineering jobs outside DLT
DLT need to be matured to handle wide variety of integrating source & target, currently only support DELTA table in databricks. Expecting that be supported for any tool/service/product which supports DELTA format filesystems
Job clusters can't be reused even for the same retry in PRODUCTION, since shutdown immediately after the job run/fail is set by default - Need to check any options to increase this limit
Multi-Task jobs requires TASK output should be passed to next input TASK and also need to support FAIL on trigger and setting OR dependent predecessors to trigger ,Currently supports only AND
No serverless option for Data engineering jobs outside DLT
DLT need to be matured to handle wide variety of integrating source & target, currently only support DELTA table in databricks. Expecting that be supported for any tool/service/product which supports DELTA format filesystems
What problems is the product solving and how is that benefiting you?
Easier integration from various source system starting from IOT, Streaming connectors & batch connectors
Helpful to easily design the lakehosue medallion architecture RAW, REFINED AND GOLD to contextualize the enterpise common data model & warehosue systems
Data quality expectations in DLT is very helful to speed up the quality check process & displays in monitoring dashboard lineage process.
Auto tuning - compaction is helpful along with VACCUM
Able to integarted metastore well with Collibra for data governance
Helpful to easily design the lakehosue medallion architecture RAW, REFINED AND GOLD to contextualize the enterpise common data model & warehosue systems
Data quality expectations in DLT is very helful to speed up the quality check process & displays in monitoring dashboard lineage process.
Auto tuning - compaction is helpful along with VACCUM
Able to integarted metastore well with Collibra for data governance
Scalable, fast and easy to use
What do you like best about the product?
Databricks delta lake is the default storage for databricks which makes it very useful. Time travel, transaction, partitioning makes it very efficient.
What do you dislike about the product?
Until now I have not faced any limitations for my use case.
What problems is the product solving and how is that benefiting you?
We are using databricks lakehouse to manage batch and realtime data pipeline to fetch data from elasticsearch & Azure datalake.
Very friendly with Jupyter users.
What do you like best about the product?
Data Engineer & Machine Learning is very easy to use.
What do you dislike about the product?
It takes time to start a job cluster so I must create a cluster for live update dashboard.
What problems is the product solving and how is that benefiting you?
Schedule ETL jobs.
Many teams can use with different programming languages.
Many teams can use with different programming languages.
Databricks lakehouse
What do you like best about the product?
Everything is on a single platform like ETL, Sql dashboard and running ML models.
Simplied version for creating scheduled jobs using workshops and the best part is Delta Lake.
Simplied version for creating scheduled jobs using workshops and the best part is Delta Lake.
What do you dislike about the product?
Every piece of code should be in the form of notebooks which sometimes makes it difficult to manage. It can be more user friendly if they give different options.
What problems is the product solving and how is that benefiting you?
Time travel feature allows to version database instead of keeping redundant or replicas. This has optimized both in terms of human efforts and cost.
Lakehouse is the Marriage of cloud based DW and Data Lake
What do you like best about the product?
It is a cloud native modern data estate service which handles core DW concepts around competing with snowflake and delta live table schema requirements like CDC like a champ
What do you dislike about the product?
Lakehouses are great but not the answer to everything when it comes to all the needs of cloud scale analytics and AI
What problems is the product solving and how is that benefiting you?
Lakehouse model enables you to work in a truly unified architectyou are that provides highly performant and structured streaming capabilities, and most importantly for me, data science, machine learning and Visualization capabilities.
Databricks Lakehouse is one shop stop any bigdata analytics
What do you like best about the product?
Databricks lakehouse is one shop stop for analytics with Big data case
What do you dislike about the product?
Databricks have many releases one going and that might create a need for customer to constantly updates there infrastructure
What problems is the product solving and how is that benefiting you?
It helps optimise Spark engine by building a wrapper compute on Spark cluster and this help run huge volume based queries much faster
One Stop Shop for Data Engineers
What do you like best about the product?
One platform to access Notebooks, tables, AI/Ml Platform
What do you dislike about the product?
No debugger like other IDE's, difficult to navigate notebooks and functions
What problems is the product solving and how is that benefiting you?
Formed Datalake to reduce efforts and time for internal teams
Easiest way to onboard to spark and other advanced analytics
What do you like best about the product?
I love that Databricks abstracts away all of the administrative overhead of running spark clusters.
What do you dislike about the product?
I wish that spark could do run time partition elimination
What problems is the product solving and how is that benefiting you?
1. data mobility 2. data latency 3. workload isolation
One Stop Shop Unified Analytics Platform..
What do you like best about the product?
The concept of a lakehouse and the simplicity this brings.
I like the notebook functionality and the constantly expanding ability of Partner Connect and link to BI tools
I like the notebook functionality and the constantly expanding ability of Partner Connect and link to BI tools
What do you dislike about the product?
It feels like an Integrated Development Environment would be a fantastic improvement to the existing UI.
Dbx might help accomplish this with further developments.
Dbx might help accomplish this with further developments.
What problems is the product solving and how is that benefiting you?
the lakehouse is very powerful and solves a lot of early issues with having a separate data warehouse/data lake and utilising Delta Lake enables it to be ACID compliant.
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