Oracle Autonomous Data Warehouse vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
Oracle Autonomous Data WarehouseSAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Oracle Autonomous Data WarehouseSAS Data Management
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
Oracle Autonomous Data WarehouseSAS Data Management
Top Pros
Top Cons
Features
Oracle Autonomous Data WarehouseSAS Data Management
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Oracle Autonomous Data Warehouse
-
Ratings
SAS Data Management
8.3
10 Ratings
1% above category average
Connect to traditional data sources00 Ratings8.610 Ratings
Connecto to Big Data and NoSQL00 Ratings8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Oracle Autonomous Data Warehouse
-
Ratings
SAS Data Management
6.7
8 Ratings
22% below category average
Simple transformations00 Ratings6.18 Ratings
Complex transformations00 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Oracle Autonomous Data Warehouse
-
Ratings
SAS Data Management
6.7
8 Ratings
19% below category average
Data model creation00 Ratings5.56 Ratings
Metadata management00 Ratings7.47 Ratings
Business rules and workflow00 Ratings6.67 Ratings
Collaboration00 Ratings7.07 Ratings
Testing and debugging00 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Oracle Autonomous Data Warehouse
-
Ratings
SAS Data Management
7.9
9 Ratings
4% below category average
Integration with data quality tools00 Ratings7.69 Ratings
Integration with MDM tools00 Ratings8.27 Ratings
Best Alternatives
Oracle Autonomous Data WarehouseSAS Data Management
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10
Skyvia
Skyvia
Score 9.6 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.2 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Oracle Autonomous Data WarehouseSAS Data Management
Likelihood to Recommend
8.9
(32 ratings)
7.6
(11 ratings)
Likelihood to Renew
8.0
(1 ratings)
9.0
(2 ratings)
Usability
-
(0 ratings)
6.0
(2 ratings)
Performance
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
7.7
(6 ratings)
Implementation Rating
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
Oracle Autonomous Data WarehouseSAS Data Management
Likelihood to Recommend
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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SAS
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
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Pros
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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SAS
  • SAS/Access is great for manipulating large and complex databases.
  • SAS/Access makes it easy to format reports and graphics from your data.
  • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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Cons
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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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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Likelihood to Renew
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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SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
Oracle
No answers on this topic
SAS
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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Performance
Oracle
No answers on this topic
SAS
It worked as expected.
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Support Rating
Oracle
No answers on this topic
SAS
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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Implementation Rating
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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SAS
No answers on this topic
Alternatives Considered
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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SAS
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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Return on Investment
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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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
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