

Overview
What is Oracle Autonomous Data Warehouse?
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.…
Oracle Autonomous Data Warehouse for Enterprise Analytics
A quick way to analyze your data
Oracle Data Warehouse provides enough functionality for basic data warehousing transformations
New era of data warehouse
Must Use Tool for any Datawarehouse Business Intelligence Developer
The current purpose of using …
The future of databases
Oracle Autonomous Data Warehouse An Awesome Tool That Gets Better The More Your Organization Uses It
Your own Datawarehouse on a few clicks. Fast and easy to provision and configure.
First hand with Oracle Autonomous Data Warehouse
Oracle ADWH for manufacturing company
New-generation data warehousing and analytics with Oracle Autonomous Data Warehouse
ADW review
Harness the Autonomous Data Warehouse--the best Oracle data warehouse solution!
Awesome in-house solution!
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Pricing
What is Oracle Autonomous Data Warehouse?
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…
Entry-level set up fee?
- No setup fee
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- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
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Alternatives Pricing
What is Amazon Redshift?
Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
What is retailMetrix?
RetailMetrix is a data analytics platform for retailers with the mission of enabling retailers to get value from their data. RetailMatrix processes and stores sales, labor and customer data using data warehouse technologies. Its dashboards and reports allows team to find the data that matters to…
Product Details
- About
- Competitors
- Tech Details
- FAQs
What is Oracle Autonomous Data Warehouse?
Oracle Autonomous Data Warehouse Competitors
- Amazon Redshift
- Microsoft SQL Server
- SAP Business Warehouse (SAP BW), formerly SAP NetWeaver Business Warehouse
Oracle Autonomous Data Warehouse Technical Details
Operating Systems | Unspecified |
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Mobile Application | No |
Frequently Asked Questions
Comparisons
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Reviews and Ratings
(240)Attribute Ratings
Reviews
(1-25 of 32)Nice
- Querying & Extraction of Data
- Data modelling
- Materialised views and views creating
- More user interactive
- Syntax rectifying capability
- UI
Oracle Autonomous Data Warehouse for Enterprise Analytics
- It is easy to setup.
- It is easy to manage.
- Database admin with limited experience can manage.
- Performance.
- Connectivity with third party tools needs to be improved.
- No on-prem solution.
A quick way to analyze your data
- Fast performance
- User friendly
- Fully managed
- Data security
- More data connection to different applications can be introduced
- Pricing
- User support service
Oracle Data Warehouse provides enough functionality for basic data warehousing transformations
- transformations
- ease of use
- Oracle Data Warehouse creates a package in the database for each mapping - it would be nice to have the ability to manually update that package and Oracle Data Warehouse to recognize those updates without problems
New era of data warehouse
- Excellent performance, ease of use, great scalability, and most importantly excellent integration with Oracle GoldenGate for real-time data view
- Fully managed enterprise class, full-featured relational database that brings the power of Oracle technology to managed Cloud; support for private endpoints to keep data private
- Multi-user, high concurrency real-time reporting from across several data sources
- 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
- Drive innovation
- Cost management
- Create internal/operational efficiencies
- Improve business process outcomes
- Improve supplier or partner relationships
- Improve compliance and risk management
- Improve customer relations/service
- Improve business process agility
The current purpose of using Oracle in our team is just for storing less data but highly index database for frequent data fetch which enable our operation to resolve customer tickets/complaint within SLA. Our current system is small which may we scale in the future (10-20 million records in main and we also create SCD type 1,2 and 3 ETL flow using Oracle).
- To work in SQL and PL SQL and create high index database. Its user base is very huge so it is used in most of the company which helps in building profile.
- Easy integration in application development, I have used in python currently.
- Developers must know the backend as well so that they can build a scalable product.
- If you learn SQL using Oracle, which cover most of the syntax, then you will be proficient in SQL and can easily work on other tools too (for ex, MySQL and PostgreSQL).
- In Oracle Data Warehouse I used to build Type 1 and Type 2 Load frequently, where I did not face any issue, so nothing to improve from a product functionality point of view.
- If UI is more interactive as in Informatica, then maybe more users can start using this
- Blog link must be there on one site for solving user issues.
We build a small review system where work table loaded using API and then cluster other processing stuff done on the work table and data saved to stage table and final SCD type 1 load to base table. This is ultimately used by the Operations team for solving end-user queries.
The future of databases
- Out-of-the-box use
- Flexibility of scaling out and in
- Minimal DBA intervention required to run the system
- Exposure of the OS on request basis
- Delegate control of the Oracle binaries on an as-needed basis
- View access of the OS which may be used for troubleshooting purposes
- Ease of use is one of the best features
- Low initial investment
- Better performance and highly scalable
- Self correcting and automatic maintenance
Oracle Autonomous Data Warehouse An Awesome Tool That Gets Better The More Your Organization Uses It
- fully autonomous
- Easy to use
- Fast query performance
- Complicated and time consuming setup
- Several discovery calls are needed in order to begin process
- Oracle customer service is not always responsive
- Simple and quick provisioning and configuration
- Really good and fast ETL features allow quick data load
- Always pached, always available. Foerget about many tedious admin tasks
- Pricing may we high when using all features
First hand with Oracle Autonomous Data Warehouse
- Scale Up & Down as you need to reduce the cost immediately.
- Save lots of time and costs, helped project delivery in less time which is a big plus for customer and vendor. Also, saving administrative cost.
- Performance Tuning, security, backup and high availability.
- Combine the abilities of a data lake and a data warehouse to manage any data type for business analysis.
- The analytics come with it to code collaboratively with the rest of your team, not the classic data miner GUI interface.
- Due to security limitations, neither the powerful GUI development environment Application Express (yet?) nor Oracle R Enterprise are not available.
Oracle ADWH for manufacturing company
For the project, we proposed them an Oracle cloud full-stack architecture based on:
- Object storage
- Oracle Autonomous Data Warehouse
- Oracle Analytics cloud
- Export of data from the company ERP on flat files
- Creation of a staging area layer
- Creation of PL/SQL procedures to import files on staging structures, performing formal checks, cleaning and standardization processes
- Creation of entity-relation models for some Data Marts
- Creation of ETL flows to load data from the staging area on the Data Marts
- Creation of a series of institutional reports, based on Data Marts
- Profiling of users to access to the reporting layer and for free ad hoc analysis
- It's really fast to set up (like 2 minutes to create a new database)
- It's cheap, and its costs are based on dedicated resources (RAM and CPUs), and it can eventually be turned off
- Resources (RAM and CPUs) can be increased or decreased at run-time
- Patching and release upgrades are automatically performed by Oracle at scheduled times
- It's secure, without the need to implement a VPN: it provides a wallet that includes encryption methods for authentication
- It automatically extracts statistics (needed by Oracle database engine to improve performances) on its structures
- Backups are automatically performed and very easy to restore
- Disaster recovery is granted thanks to fault domains provided by Oracle
- It's really limited from a DBA point of view
- There is only 1 tablespace associated to all the users you create on the database
- The cost (license and monthly fees) are not always very clear
- The loading of data on the cloud is subjected to network speed, so huge amounts of data may take a lot of time to be loaded on the database
It's probably less suited for very big companies with huge amounts of data, for network latency in moving data through the network, or for companies that already have very big Data Warehouse on-premise, and want to migrate it into the cloud, since Autonomous database has some limitations.
New-generation data warehousing and analytics with Oracle Autonomous Data Warehouse
- Extremely fast query execution for large volumes of data
- Very rich library of statistical and aggregation functions
- We can access the underlying data objects from Multiple IDEs such as SQL developer
- Highly granular and robust access control on data warehouse objects
- Sometimes when we run queries the error codes/details are not detailed or very helpful
- We need a built-in easy-to-use data pumping tool
- I get confused sometimes between the schema vs user in Oracle Autonomous Data Warehouse (it is the same)
- For a large volume of data and quick results, Oracle Autonomous Data Warehouse is best
- You can choose columnar storage options to persist data
- No learning curve if you have already used Oracle SQL
- Self-maintenance and auto-scaling based on usage and load
ADW review
- This eliminates nearly all the manual and complex tasks that can introduce human error
- Database providing built-in support for multi-model data and multiple workloads such as analytical SQL, machine learning, graph, and spatial.
- I need to spend lot a time to find the appropriate technical document
- Pricing
Business problems that it addresses: Since the manual work is almost completely eliminated, the cost of administering a data warehouse is reduced significantly. Also, this is highly secured and reliable.
- High performance using continuous query optimization, table indexing, data summaries, and auto-tuning
- Autonomous data encryption and security patch application
- Different deployment models--shared, dedicated, and cloud@customer
- Built in analytics--this makes data loading, indexing, and building good data visualization models easier
- Improved machine learning capabilities
- I find it to be the best autonomous solution out there with high scalability and reliability
- More capabilities of Analytics Cloud
1. High performance is needed--The autonomous data warehouse is capable of increasing performance for continuous query optimization, table indexing, data summaries, and auto-tuning even as data volume and number of users grows.
2. High scalability is needed--Unlike other cloud services that require downtime to scale, Oracle Autonomous Data Warehouse scales while the service continues to run.
3. Automation is needed--Oracle Autonomous Data Warehouse automates provisioning, configuring, securing, tuning, and scaling for a data warehouse.
Less suited when
1. There is not a significant amount of data that needs to be handled on a daily basis.
2. Data analytics is not a requirement.
Awesome in-house solution!
- Integration with other Oracle products is very easy.
- Centralizing different data formats.
- Smooth implementation.
- Learning curve can be high if the user is inexperienced.
- Can get expensive with options.
Great for digital data but sharing can be complicated
- Store data and information
- Help process automated tasks
- Break down complex projects
- Save time on manual tasks
- Processing times can use some optimization to add flexibility
- The complexity of the tool doesn't allow a more widespread usage by partners
- It's great for digital but could be improved to be better used with other data sources
Oracle Data Warehouse in our data lake (Real scenario)
- Performance is really nice if set properly.
- [Reliability].
- Documentation is easy.
- Some ETL tools are not compatible yet.
- Even they have a good documentation, I don't think this is well structured.
- The tool could be more intuitive.
Oracle Autonomous Data Warehouse + Oracle Analytics Cloud + Oracle Blockchain Platform = 🥰
Let's start with the most engineer-y one: JSON or SQL? It does not matter. Basically, the DB hides the fact if data is in SQL or JSON structure and allows you to easily make queries independently of the actual data structure. This is extremely useful as in our case the Blockchain provides structures in JSON and we needed to digest the information without wanted to dump everything into a strict SQL table! And that works out of the box.
- Connecting to Oracle Blockchain Platform out of the box
- JSON or SQL? ADW makes handling both as if they are the same!
- The basic setup comes with quite some power. The power is often too much for a data warehouse which is used to aggregate data just a dozen times per day and is due to caching not queries for the data sets that often. A smaller shape - yet bigger than the always free - would be great!
The Oracle Autonomous Data Warehouse - My dream come true
- 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.
- Not sure what these can be
- data warehouse and data lake projects
- storage of decommissioned applications/databases if you one day would like to restore data - then you will always have the data available.
ADW is a fantastic cloud data warehouse
- Data warehouse in-cloud, that is the biggest plus point.
- No need to worry about backups or maintenance since it is in-cloud.
- Oracle Analytics Cloud comes with a default connector to ADW which makes it handy in terms of integration. OAC is our reporting tool that sits on top of ADW.
- ODI Marketplace is a free add-on that can be installed on the compute of ADW and could be used as a complete ETL tool.
- Oracle ADW should definitely improve in terms of cumbersome connectivity with third-party tools like ODI Marketplace.
- Oracle Data Sync that is used to load data into ADW does not work if we have single sign-on enabled.
- ADW can also be priced on a subscription basis instead of universal credits. This way customers need not be hooked all the time concerned about overages but use the tool to its full capacity.
Not the most affordable data warehousing solution
- Quick and easy deployment. There is no hassle in setting up software and maintaining hardware.
- Highly available and scalable. Accessing the data warehouse is easy, and it can scale up based on the data size requirements.
- Autonomous functionality. With the help of machine learning, autonomous data warehousing reduces the amount of time spent managing it.
- Customer support isn't the best out there. We usually have to wait about an hour to get some form of assistance.
- Pricing is a bit higher than many of its competitors such as AWS Redshift.
- Tweaking features requires dedicated staff. Software is fairly advanced. Would be difficult to use for newcomers.
A high performance warehouse database
- It enables us to execute large queries quicker
- It is easier to set up
- It is easier to manage
- I want more admin access for DBA to configure this database
Inside review on ODW.
Reporting is one of the major requirements across the org and Oracle Data Warehouse helps us keep the history and dimensionality and scaling.
- Rending data from all different dimensionalities
- Sstable, does not hang up
- Ease of use
- Transformation of data
- Built-in analytics
- Seamless integration with cloud
- To integrate multiple sources into one warehouse.
- Rendering data
- Ease of debug
- When competing with BDD or any other big data tools where there is not need of a data warehouse.
Oracle Autonomous Warehouse Review
- Read queries
- ETL process
- Performance.
- Use case for hybrid environment
- Price factor
- Clustering
Oracle Data Warehouse is the 800 Pound Gorilla
- Handles workloads like a champ.
- Uses state-of-the-art analytic functions and allows for quick, easy SQL.
- "Secret Sauce" integrates the hardware and the software for faster I/O.
- Supports thousands of concurrent users.
- We had issues converting a legacy DW (with its existing indexes, etc) over to the new DW hardware. Given the memory-intensive resources, not all indexes are advised. Traditional query tuning methods do not work. You have to re-learn some tuning tactics.
- Given the number of features it has, it is far more complex to administer. Requires trained staff to support.
- Support in these areas is generally poor. Oracle is, sadly, no exception.
- I HATE the current push to the cloud. Seems like a gigantic money-grab.