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.
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Teradata Vantage
Score 8.3 out of 10
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Teradata Vantage is presented as a modern analytics cloud platform that unifies everything—data lakes, data warehouses, analytics, and new data sources and types. Supports hybrid multi-cloud environments and priced for flexibility, Vantage delivers unlimited intelligence to build the future of business.
Users can deploy Vantage on public clouds (such as AWS, Azure, and GCP), hybrid multi-cloud environments, on-premises with Teradata IntelliFlex, or on commodity hardware with VMware.
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.
Teradata Vantage is well suited for large scale ETL pipelines like the ones we developed for anti money laundering risk matrices. It handles heavy joins, aggregations, and transformations on transactional data efficiently. We generate alert variables, adjust for inflation, and monitor establishments monthly with it, all integrated with Python and Control-M for a centralised automation across the company. For less appropriate, I would say that heavy resource demands might slow down experimentation for iterative work.
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.
Level of integration or compatibility to connect it to different applications can be improved
The support service is slow
The issue is with the record number limitation of not being able to bring back more than one million records or not being able to export larger datasets to Excel
Teradata can improve by supporting more native AWS cloud features. Currently if a node goes down the EC2 instance must be restarted. It isn't something that happens frequently but more tight integration with cloud providers like AWS and Azure will allow Teradata to offer truly dynamic scaling.
Some Teradata features are oversold before they are ready for prime-time. Teradata is not unique in this but if something is sold as an integrated product stack it should really be integrated not something that requires an extensive development cycle to be integrated at a customer's expense. If something is supported it should've really be tested and QAed thoroughly before a customer touches it.
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.
Teradata is a mature RDBMS system that expands its functionality towards the current cloud capabilities like object storage and flexible compute scale.
Teradata Vantage allows us to create a scalable infrastructure to support our strategic initiatives. The dedicated compute power ensures reliable performance with isolated workloads and dedicated resources, optimizing workflows for faster, more efficient data transfers. The compute clusters support ETL processes and OSF’s developers and data science team with the flexibility to create self-service analytics, to spin up/down at any time, driving better performance and minimizing costs.
We have meetings at the beginning with the technical team to explain our requirements to them and they were really putting in a lot of effort to come up with a solution which will address all our needs. They implemented the software and also trained a few of our resources on the same too. We can get in touch with them now as well whenever we run into a roadblock but it's very less now.
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.
Our organization adopted Oracle almost 20 years ago and there were a few options at that time. Oracle was the leading database tech company at that time and it was a safe choice to us. And they have been evolved and always ahead of new technologies, high performance, and professional business support. We didn't find a good reason to replace Oracle with any other competitors.
Teradata is way ahead of its competitor because of its unique features of ensuring data privacy and data never gets corrupted even in worst case scenario. In most cases, the data corruption is a major issue if left unused and it leads to important data being wiped off which in ideal case should be stored for 3 years
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.
Teradata is been absolutely phenomenal for our project because we feed huge chunks of data to it and get back the desired results in no time which earlier used to take hours to process and then also sometimes timeout.
We don't have to do any manual intervention for resource or task allocation, it is all taken care by Teradata internally and all the AMP's are given equal amount of work and have their own resources to complete them with no sharing with another.
