Databricks Lakehouse Platform vs. Oracle Autonomous Data Warehouse

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Lakehouse Platform
Score 8.1 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Oracle Autonomous Data Warehouse
Score 9.0 out of 10
N/A
Oracle Autonomous Data Warehouse is optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can discover business insights using data of any size and type. The solution is built for the cloud and optimized using Oracle Exadata.N/A
Pricing
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
No answers on this topic
Offerings
Pricing Offerings
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Top Pros
Top Cons
Best Alternatives
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Small Businesses

No answers on this topic

Google BigQuery
Google BigQuery
Score 8.7 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
Oracle Exadata
Oracle Exadata
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Likelihood to Recommend
8.4
(17 ratings)
8.9
(32 ratings)
Likelihood to Renew
-
(0 ratings)
8.0
(1 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
8.6
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Lakehouse PlatformOracle Autonomous Data Warehouse
Likelihood to Recommend
Databricks
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
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Oracle
II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.
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Pros
Databricks
  • Process raw data in One Lake (S3) env to relational tables and views
  • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
  • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
  • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
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Oracle
  • Very easy and fast to load data into the Oracle Autonomous Data Warehouse
  • Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
  • Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
  • It is always patched and always available and you can add storage dynamically as you need it.
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Cons
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
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Oracle
  • It is very expensive product. But not to mention, there's good reasons why it is expensive.
  • The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
  • Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.
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Likelihood to Renew
Databricks
No answers on this topic
Oracle
Because
  • It is really simple to provision and configure.
  • Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
  • Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.
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Usability
Databricks
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
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Oracle
No answers on this topic
Support Rating
Databricks
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
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Oracle
No answers on this topic
Implementation Rating
Databricks
No answers on this topic
Oracle
Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.
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Alternatives Considered
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
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Oracle
As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it
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Return on Investment
Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
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Oracle
  • Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
  • Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
  • All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.
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