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Oracle Autonomous Data Warehouse

Oracle Autonomous Data Warehouse

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.…

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Recent Reviews

Nice

9 out of 10
March 29, 2022
Incentivized
I used to use it in my previous role when I was working as a Spatial Data Analyst. I mostly used it to query and model GIS data and to …
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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…

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Alternatives Pricing

What is Amazon Redshift?

Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.

What is Google BigQuery?

Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

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Product Details

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 solution is built for the cloud and optimized using Oracle Exadata.

Oracle Autonomous Data Warehouse Competitors

Oracle Autonomous Data Warehouse Technical Details

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Frequently Asked Questions

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.

Amazon Redshift and Microsoft SQL Server are common alternatives for Oracle Autonomous Data Warehouse.

The most common users of Oracle Autonomous Data Warehouse are from Enterprises (1,001+ employees).
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Reviews and Ratings

(242)

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Reviews

(1-25 of 32)
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March 29, 2022

Nice

Score 9 out of 10
Vetted Review
Verified User
Incentivized
I used to use it in my previous role when I was working as a Spatial Data Analyst. I mostly used it to query and model GIS data and to write spatial queries to extract meaningful information. We used a GIS product that was only compatible with oracle and TOAD. I had some fun learning/experiences with it.
  • Querying & Extraction of Data
  • Data modelling
  • Materialised views and views creating
  • More user interactive
  • Syntax rectifying capability
  • UI
It has always been well suited to me while writing spatial and nonspatial oracle SQL queries to extract some meaningful data. It made my life easier to write queries etc. The good thing is that it has got heaps of documentation available online and also tutorials which are good for learning purposes. Bad in the sense that probably can be improved in terms of UI
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse was tested for specific reporting use cases. It was tested to see how efficient it is when compared to our current existing solution. Also, we have a requirement to keep the database up and running 24x7. The autonomous data warehouse setup and maintenance are very simple and easy, it will help to manage resources efficiently.
  • 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.
It is well suited for analytical reporting, data lake, and read-intensive databases. I have faced some issues with integration and connecting to third-party tools.
Prashast Vaish | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is being used by our organization to help our clients get the best out of their data which was earlier analyzed using Microsoft Excel. It is currently being used by one department of the company which caters to an Australian insurance giant. The clients want to better utilize the claims data in order to reduce the pathing cost and increase income from recoveries.
  • Fast performance
  • User friendly
  • Fully managed
  • Data security
  • More data connection to different applications can be introduced
  • Pricing
  • User support service
It is well suited for scenarios where large data sets are to be analyzed and insights to be extracted. It is not suitable for translations like update, delete, etc as it is not optimized for this. The major purpose of a data warehouse is to handle large sets of data to efficiently analyze them to help businesses.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
It's used by a department, it moves and transforms data from transactional financial database into warehouse database, so that end users can generate the reports out of it.
  • 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
It works good for data movement and transformations into data warehouse databases.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is a fully managed database that’s tuned and optimized for data warehouse workloads, so we decided to give it a try with a POC. It combines the market-leading performance of Oracle Database with the ease of Autonomous Database and is self-driving, self-securing, and self-repairing. Our objective was to spend our time focusing on delivering applications to solve our business problems. One of the hurdles was the time spent in maintaining--upgrading, patching, installing new services. Oracle Autonomous Data Warehouse gave us the confidence to delegate the operational well-being of our database instances to the experts who designed it from the ground up.
  • 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
The ease of use for our team, their ability to create their own data flows and bring in data sets, the function option for users with limited SQL experience.
  • 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

Not suited: Nothing really. Now with the latest version; it is super stable and fast.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
It is used in multiple departments to build in-house analytics tools where we use Oracle as our main database.
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.
Create a whole review system that requires work table, stage table, and History table and OLAP table. In Oracle Data warehouse this is very easy, fast, and with a high user base you can get many solutions implemented by looking online. Building complete end-to-end data pipeline and updating old tables is very easy. Integration with other applications or loading data using an external API is very hassle free task.

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.


December 23, 2020

The future of databases

Jyoti Shah | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is used by the IT department . It is an automated version of Oracle Database. It removes the mandate layer of a database administrator to manage the database.
  • 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
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is being used by our company to full manage our warehouse inventory. Time that was wasted previously doing repetitive tasks is now delegated and we did not have to worry about any database management.
  • 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
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.
Lisandro Fernigrini | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I'm using the a Free Tier [Oracle] Autonomous Data Warehouse in a PoC / Test environment to centralize information from a wide range of sources in order to allow quick Reporting and OLAP analysis of data coming from our suite of tolling software. I'm integrating information from more than 30 databases (20 SQL Server, 5 Oracle and other like Postgres). This POC will try to demonstrate the ease of use and maintenance of Autonomous databases so we can recommend them to our customers.
  • 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
It's great if you are already using othe Oracle Cloud products. It is really simple to integrate with them. We plan to use it as a central datawarehous hosting data from many different data sources.
Krishan Mohil | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
<h3><span style="font-size: 15px; color: rgb(21, 21, 33); font-family: &quot;Source Sans Pro&quot;, sans-serif; font-weight: 500;">One of the biggest challenge is the scaling and provisioning of hardware &amp; software for any data ware house solution and also the associate problems like configuration, security and importantly tuning of the storing and fetching/querying data. For the same reason Oracle Autonomous Data Warehouse tool used for one of the project for the customer. It help overcome some of critical, complex, manual and time consuming tasks like hardware procurement, configuration, security, high availability and high performance all this with reducing administrative cost and no human error.</span></h3>
  • 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 Autonomous Data Warehouse] is well suited in most of case when it comes to save time, cost, quick project delivery, over the cloud and instant scale up and down features. I would not say scenarios where it is less appropriate, it always with anything which comes news have some features missing or not available as of time, you can find ways for better analytics or other ways than no support for R language.
Paolo Borghi | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
A manufacturing company recently asked my company to do a Business Intelligence project to improve and standardize the analysis of its users. Before the project, users used spreadsheets and local databases based on Access to perform management analysis.
For the project, we proposed them an Oracle cloud full-stack architecture based on:
  • Object storage
  • Oracle Autonomous Data Warehouse
  • Oracle Analytics cloud
After a first as-is analysis, the project steps have been:
  • 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
The project has recently been deployed and the architecture is currently being used by about fifty users.
  • 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
Oracle Autonomous Data Warehouse is particularly well suited for small or medium-sized companies that are evaluating a new database for reporting goals or for creating a common data access point for the whole enterprise.

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.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We are using Oracle Autonomous Data Warehouse for storing our data from various fusion apps, marketing technology stack, and customer transaction data. We are stitching these disparate data sources/systems together so that eventually we can perform historical and OLAP analysis using Tableau.
  • 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)
  1. For a large volume of data and quick results, Oracle Autonomous Data Warehouse is best
  2. You can choose columnar storage options to persist data
  3. No learning curve if you have already used Oracle SQL
  4. Self-maintenance and auto-scaling based on usage and load
December 10, 2020

ADW review

Yogeswar Reddy | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use the Oracle Autonomous Data Warehouse as my company central data warehouse where we store the different department's data in corresponding tables
  • 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
Suitable data warehouse with all necessary components
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is used in automation of provisioning and configuring a data warehouse. It is also used to tune and scale the data warehouse as needed. It is used across the whole organization.
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
Well suited when
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.
Duncan Hernandez | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
The blockchain style for data storage and analysis. We have many different data formats from XML, HTML, JSON and this tool is very useful in organizing and querying all types of data at once. Getting all of our data centralized in one place and then only using one tool to look at all of it is hugely beneficial.
  • 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.
Again, it is great for consolidating our data. It performs much better than our last tool. Our reports are smooth and we are able to integrate more data within each report. This is huge because this is the ideal outcome of a product like this. We haven't moved all of our ETL to the tool yet, but any new pipelines being built are utilizing the tool.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Our organization uses Oracle Autonomous Data Warehouse to store, update, and, most importantly, automate tasks. It's very efficient when working with digital data, specifically online conversation data and transaction information.
  • 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
It's great for digital data. The data sharing processes can be complicated when using multiple data sources, so oftentimes you need experts to help with implementations and it can get expensive and time consuming.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
One of our data warehouses is Oracle Autonomous Data Warehouse and it is being used for two years corresponding very well in terms of performance and reliability. Some of our data has been stored there and it's available to some departments to connect through it to pull data feeding their business intelligence tools.
  • 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.
You definitely should go for Oracle Autonomous Data Warehouse if you are looking for something trustable, secure, tunable and that can be scalable easily. All these features make it one of the best tools in terms of Data Warehousing. If you are looking for something small and of course cheap, I would not suggest this option.
Peter Merkert | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use ADW in conjunction with the Oracle Blockchain Platform, as it provides an easy way to inspect, analyze, and reuse information stored in a blockchain style. The ADW has basically the same functionality as the Oracle Autonomous Transaction Processing - and they have a massive toolset of useful things!
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!
We use ADW to stash data long term from the Oracle Autonomous Transaction Processing and also to digest and process data in a fast manner from the Oracle Blockchain Platform.
Erik Dvergsnes | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
We use Oracle Autonomous Data Warehouse for one specific application that store[s] alarm[s] and incidents as an historical database. It address business problem[s] with regard to preventive maintenance that analysts can query more than a billion rows very fast, to identify certain patterns. This historical database was migrated from an older Oracle database into the Autonomous Data Warehouse and now we don't need to think about upgrading the database and having machine/database available. Now the database is always available and if it is not need[ed] for some time, we just stop it, and when there is need to query the data I start it up again.
  • 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
Very well suited for:
- 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.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Oracle Autonomous Data Warehouse is the data warehousing tool for our company in cloud. It is currently being utilized by the transportation department, but we are in the process of expanding its adoption to other departments once the single sign-on issues with the connection to our core Oracle ERP Cloud is resolved. We have a need for many summary reports which could be a challenge from OTBI, hence we are planning to do summarization at the ADW level and then report out of ADW using Oracle Analytics Cloud.
  • 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.
Oracle Autonomous Data Warehouse is well suited for on-prem to cloud situations. That is more controllable as we have control over the ETL tools and database. It is still a challenge to adopt ADW on a full scale for cloud-to-cloud implementations primarily because the tool is still evolving and the challenges pose a risk to critical implementations without resolving the challenges.
Score 6 out of 10
Vetted Review
Verified User
Incentivized
Oracle Data Warehouse is being used across our entire organization. Although each department in our organization has its own individual use cases for maintaining a data warehouse, the overall problems that are being solved are the same. We are using Oracle Data Warehouse for business intelligence related queries, finding trends in periods of time using all the historical data, and for deep data exploration.
  • 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.
Oracle Data Warehouse is well-suited for businesses medium-sized and up. Keep in mind to manage and utilize Oracle Data Warehouse's full potential, you will need to hire dedicated staff that is experienced in using it. Not to mention, the pricing is a bit high. It is less appropriate for smaller businesses that have smaller budgets and fewer employees.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
The autonomous data warehouse is being used as a test case currently. We are using it to test how much more efficient and reliable it can be compared to our current configuration. It is used solely in my department . It is used to address performance issues for the most part.
  • 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
It is well suited when buying new server hardware is too costly and when setting up a warehouse quickly is very necessary. It is also great when a DBA has very limited experience managing a data warehouse.
September 18, 2019

Inside review on ODW.

Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use Oracle Data Warehouse for integrating all the dist data that gets generated from ERP systems to the warehouse and then use the normalized data for reporting purposes. We use Oracle BI reporting for the whole organisation. We deliver reports for all the verticals in our organisation starting from financials, HR, procurement, ridership and so on. There is also an other ERP that is called Maximo and the transaction data gets processed in Oracle Data Warehouse.

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.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We used Oracle Autonomous Database for our warehouse reporting. It is a 50 TB huge database and reports are generated every day. It is pretty read intensive database. It's availability is required for 24 X 7. We have several thousands customers using it on a regular basis. The performance is phenominal.
  • Read queries
  • ETL process
  • Performance.
  • Use case for hybrid environment
  • Price factor
  • Clustering
We used Oracle Autonomous Database for our warehouse reporting. It is a 50 TB huge database and reports are generated every day. It is a pretty read intensive database. Its availability is required for 24 X 7. We have several thousands of customers using it on a regular basis. The performance is phenomenal.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We've recently adopted Exadata as our primary DW solution. It allows us to quickly store and query lots of data. The data is generally written in overnight batches and is constantly queried 24x7. It even supports some online business decisions to our customers. We use it company-wide. I am an administrator of the database, as well as a SQL Programmer.
  • 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.
Oracle Data Warehouse is, in my opinion, the best solution available. My hesitance to recommend it would be that it costs a fortune and other vendors would likely work well for smaller companies. For large companies that can afford the pricetag, you likely won't find anything to out-perform Oracle. I've seen POCs where the competition outshines Oracle, but I believe they are specific situations, and in general, I would give Oracle my recommendation (again, if money is not an object).
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