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
Oracle Exadata
Score 9.8 out of 10
N/A
Oracle Exadata is an enterprise database platform that runs Oracle Database workloads of any scale and criticality with high performance, availability, and security. Exadata’s scale-out design employs optimizations that let transaction processing, analytics, machine learning, and mixed workloads run faster. Consolidating diverse Oracle Database workloads on Exadata platforms in enterprise data centers, Oracle Cloud Infrastructure (OCI), and multicloud environments helps organizations increase…
$2.90
Per Unit
Amazon Redshift
Score 8.9 out of 10
N/A
Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
$0.24
per GB per month
Pricing
Oracle Autonomous Data Warehouse
Oracle Exadata
Amazon Redshift
Editions & Modules
No answers on this topic
Database Server
$2.9032
Per Unit
Quarter Rack
$14.5162
Per Unit
Redshift Managed Storage
$0.24
per GB per month
Current Generation
$0.25 - $13.04
per hour
Previous Generation
$0.25 - $4.08
per hour
Redshift Spectrum
$5.00
per terabyte of data scanned
Offerings
Pricing Offerings
Oracle Autonomous Data Warehouse
Oracle Exadata
Amazon Redshift
Free Trial
No
No
No
Free/Freemium Version
No
No
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Oracle Autonomous Data Warehouse
Oracle Exadata
Amazon Redshift
Considered Multiple Products
Oracle Autonomous Data Warehouse
Verified User
Engineer
Chose Oracle Autonomous Data Warehouse
In my personal opinion, Amazon Redshift is much better than Oracle Data Warehouse in two main ways. First, it's in the Cloud which eliminates the need to purchase and maintain dedicated hardware. Second, the pricing models for Redshift are far more flexible and affordable. …
Oracle DWH is a pure warehousing tool and does not try to include outside features into itself, unlike a few other warehousing platforms. This makes Oracle DWH much simpler to set up and ready to use.
On the other hand, most other warehousing platforms can provide slightly …
Oracle is a lot cheaper than traditional data warehouse appliance solutions, even if you get an expensive DBA who knows what he/she is doing. It definitely takes a lot more work to ensure it scales as your data size grows. While it won't scale past the terabyte sized data sets, …
Prezi is using AWS so Amazon Redshift was the obvious choice. It is fast, scalable and easy to use. Supplemented with Spark and Hive I'm completely satisfied using Redhsift. Sometimes I miss commands I used earlier on MS and Oracle SQL and the lack of procedural features is …
Compared to Oracle Data Warehouse, Redshift is a better data warehouse. However, this comes at a cost of advanced functionality and the ability to do OLTP style processing. What you gain is faster querying time and better scalability.
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.
Oracle Exadata is well-suited for environments where massive performance for Oracle databases is required. Storage indexes reduce the unnecessary I/O. Smart Flash Cache accelerates random reads/writes.
Our OLTP application demands very high concurrency. Multi-node Exadata provides high availability and zero downtime during DB patching. It comes with lots of built-in automations, so it reduces many routine tasks for sysadmins, like network, storage, and VM configuration, and it also reduces many Oracle DBA tasks, like Oracle software installation, patching, and upgrades.
If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
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.
Oracle Database : Deliver industry-leading security, high availability and scalability with Oracle Database, which has been significantly enhanced to take advantage of the Oracle Exadata Storage Servers.
Exadata Smart Scan : Improve query performance by offloading intensive query processing and data mining scoring to scalable intelligent storage servers.
Smart Flash Cache : Transparently cache 'hot' read and write data to fast solid-state storage, improving query response times and throughput. Exadata systems use the latest PCI flash technology rather than flash disks. PCI flash delivers ultra-high performance by placing flash directly on the high speed PCI bus rather than behind slow disk controllers.
Hybrid Columnar Compression : Reduce the size of data warehousing tables by 10x, and archive tables by 50x, to improve performance and lower storage costs for primary, standby, and backup databases. Query high, query low, archive high and archive low.
Infiniband Network : Connect multiple Oracle Exadata Database Machines using the InfiniBand fabric to form a larger single system image configuration. Each InfiniBand link provides 40 Gigabits of bandwidth–many times higher than traditional storage or server networks.
Petabyte Scalability : Easily scale data warehouse to support enterprise data growth.
[Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results.
[Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases
[Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store.
[Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance.
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.
The process of patching and upgrade of Exadata server components could be improved with a goal to minimize the overall effort, make it fully automated and transparent.
Improved guidelines and possibly more sophisticated tools for sizing of new Exadata servers for migration from old legacy hardware.
We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.
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.
I am comparing Exadata with the Oracle RAC database experience. In addition to Oracle RAC features, Exadata provides automatic performance optimization through Smart Scan and storage indexes. Deep integration with the Oracle ecosystem and tight coupling with Oracle Enterprise Manager for monitoring and management. Some downsides of Exadata are: a steep learning curve, concepts like cell offloading, IORM, and flash cache behavior aren’t intuitive initially. Operating Exadata requires specialized DBA skills.
Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
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.
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
Oracle Exadata Database Machine had the best performance overall hands down. It clearly beat the competition and we were seeing 1000X improvement on SAP HANA. Oracle Exadata Database Machine beat that without us refactoring our code. To achieve that in HANA, we had to refactor the code somewhat. Now this was for our limited POC of 5 use cases. Given the large number of stored procedures we had in Sybase, we need to capture more production metrics but we are seeing incredible performance.
Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS). Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again. Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.
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.
Single support from a single vendor with both machine and database from Oracle, which is costing us less.
With Exadata, we need less technical manpower and less technical support. A business transaction with the integrated and centralized database helps us focus on other business needs.
We don't need to buy additional licenses and Hardware for the next 3 to 5 years.
Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost.
Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time.
Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift.
