Oracle Data Warehouse

Oracle Data Warehouse

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Score 8.6 out of 100
Oracle Data Warehouse


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What is Oracle Data Warehouse?

Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse, securing data, and developing data-driven applications. It automates provisioning, configuring, securing, tuning, scaling, patching, backing up, and…

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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.

What is Amazon Redshift?

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

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Product Details

What is Oracle Data Warehouse?

Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse, securing data, and developing data-driven applications. It automates provisioning, configuring, securing, tuning, scaling, patching, backing up, and repairing of the data warehouse.

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Reviews and Ratings



(1-12 of 12)
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Score 8 out of 10
Vetted Review
Verified User
Review Source
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 8 out of 10
Vetted Review
Verified User
Review Source
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.

Score 6 out of 10
Vetted Review
Verified User
Review Source
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.
September 18, 2019

Inside review on ODW.

Score 9 out of 10
Vetted Review
Verified User
Review Source
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 7 out of 10
Vetted Review
Verified User
Review Source
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).
Score 8 out of 10
Vetted Review
Verified User
Review Source
My company is a non-profit organization of a healthcare system. We adopted Oracle Data Warehouse for building a clinical data warehouse, to support quality improvement and clinical research. Our hospitals and clinics run electronic health record systems that capture clinical data through patient care; the Data Warehouse is used to store them in a permanent manner. Once stored, the data can be normalized and standardized to be used by clinical departments, clinical champions, and researchers. There were a number of use cases in the Data Warehouse, but the major two were monitoring of clinical operation and improvement of clinical workflow.
  • Oracle Data Warehouse is a well-known and already validated product. Its performance, technical support, documentation, online community, and sustainability is the best among the area.
  • It is easy to find and hire good data developers, data architects, and analysts who specialize in Oracle Data Warehouse.
  • It is easy to develop a financial plan based on the product, as its licensing is systematic. Also, the product's scalability is well developed with licensing policy and it makes it easier to flexibly plan budgets as we need more functionalities and services.
  • 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.
Including other products, Oracle is very specialized in business support. Choosing Oracle Data Warehouse would be a safe choice for an enterprise-level company (more than a thousand employees). Healthcare organizations may want to consider Oracle, as they are typically conservative with privacy and security issues with patient data. Although cloud-based systems are widely being adopted in the healthcare industry (such as population research or genomics), core data sets (such as patients' sensitive medical records) may be better stored with a home-grown data center and warehouse solution.
August 02, 2018

My Oracle DW Review

Kartik Chavan | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
The Oracle Data Warehouse is a robust platform being used by many departments for Data Storage, Reporting from Stored Data, & also to build Marketing products. Mostly used for Analytics, as it is easy to query the data & stores a huge amount of data in a pre-processed form required for analytics of a variety of business aspects.
  • Scalable for the storage of very large data.
  • Simple queries to pull down the data compared to transactional databases.
  • Compatibility with variety of other tools, & industry support.
  • Not effective if we compare it with current Big Data applications.
  • Other warehouses are better for parallel processing.
  • Prices are high for few functionalities which are supposed to be bought separately.
For any business sectors dealing with large databases, and working on Analytics to improvise their business services, solutions or products, Oracle Data Warehouse can be a great option. The only scenario where I wouldn't recommend Oracle Data Warehouse is businesses with small databases, as it might not be very cost effective. It does provide all great functionalities including Storage services, BI Analytics, Security & more.
Score 9 out of 10
Vetted Review
Verified User
Review Source
The Oracle Data Warehouse provides a robust data warehousing platform that is used across my entire organization. Oracle Data Warehouse is directly used by a wide range of departments from analytics and data sourcing, to finance and marketing. For an organization that deals with huge volumes of data, Oracle DW is a great option for warehousing.
  • Running analytics queries is made simple on Oracle DWH.
  • Great support for large databases.
  • Even while dealing with large volumes of data, the compression capabilities of Oracle DWH ensure that most use cases are scalable.
  • While the Oracle Data Warehouse provides top notch performance, the pricing options make it unaffordable for most small and medium businesses.
  • Most add-on features that businesses can’t do without are priced separately.
  • Customizability options are limited. Cannot modify most features to suit the custom needs of Business.
For large businesses that handle very large databases, Oracle proved great performance and is probably the best warehousing option available. For small and medium business, Oracle Data Warehouse might not be the best choice to use as a warehousing platform.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Oracle Data Warehouse were used for one of our clients to act as an analytics database that stores transactional data like Financial Transaction relation information, Customer Centric Information, Sales and Purchase related Information, Projects and Service related information. The information stored in the Oracle Data Warehouse would help the key business users to pull reports through data cubes which would help them in analyzing different aspects of business. So based on the data points received and the key indicators set, it would enable the business to make informed decisions to grow their business. One example would be to identify customers sales which could be seasonal in nature, so by understanding the patterns of their previous placed order the business can vouch for the customer next time when similar conducive scenario is in place.
  • Oracle Data Warehouse is scalable and reliable.
  • Seamless integration with oracle database's using synchronous and asynchronous connectivity thus giving real time data representation to the key business users.
  • Good performance and high availability of data from the Data Warehouse for analytical reporting.
  • Like any data warehouse, one needs to conduct a cost benefit analysis to see whether the IT efforts required for implementation of the data warehouse and the cost involved in maintaining the data would be adding monetary values to the organization.
  • Data Ownership could be one concern where the management needs to decide who would be having what access to the Data Warehouse. So proper configuration of the access would be required, so that there is no breach in data ownership.
Oracle Data Warehouse will be well suited for organizations which can take the maximum advantage of the capabilities that the Data Warehouse provides. It has strong analytic reporting capabilities which need to be diligently used so that the management or the key business users are able to make the maximum use of it. Maintaining the data in Oracle Data Warehouse and implementation of the DW project would require good IT manpower and costs. So enough due diligence needs to be done before implementing Oracle Data Warehouse.
Hemant Prabhakar Patil | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Currently, we are using Oracle Data Warehouse for service analytics, sales order management and install base module analytics. Business users are using it to solve their business problems where they want to analyse & understand different service contracts made by company, products orders, sales in different territories.
  • It provides ease, feasibility and flexibility to use Oracle out of box pre-built solutions with different verticals and horizontals of industries such as Insurance Analytics, Financial Analytics, Sales and Marketing Analytics, etc.
  • It's always easy to use Oracle Data Warehouse where you have Oracle EBS and other Oracle Transactional Systems. Since it provides pre-built data models based on various standard BI solutions (in ERP & CRM Areas).
  • With various customers and businesses using Oracle dbs for transactional systems, it is always easy to recommend oracle data warehouse in numerous beneficial ways like cost, ease for implementation and maintenance, support for various top Oracle BI tools efficiently, etc
  • Query Performance in Oracle Data warehouse compared to other parallel execution dbs is a little low. But given a chance on concentration with good Oracle DB design can overcome those problems in warehouse.
  • For Big Data Implementation, it's not very cost effective compared to other big data solutions that are based on Hadoop systems and light weight BI Tools.
  • It's more preferable with Dimensional Modeling compared to 3NF models datawarehouse.
It's more preferred where ERP, CRM systems are built with Oracle and then it's always highly recommendable to use Oracle data warehouse and all Oracle solutions. It also does well with other source data systems from SAP, Peoplesoft, JD Edwards. For BI/Data warehouse solutions with Structured and Unstructured Data (Big Data Solutions) it's preferable to use Hadoop systems and other visually appealing tools.
Seth Goldberg | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
Oracle Data Warehouse was used at a previous company to be the central data warehouse. Analysts connected to it to run queries on all types of different data like customer, transaction, and behavior data. It was also used to power reporting being done by the business.
  • Strong developer toolset. e.g. PL/SQL, partitioning, compression, etc.
  • Rich syntax
  • Rock solid reliability
  • Compatibility with other tools
  • Industry support
  • More automated functionality (e.g. automated table analysis, better automated partitioning)
  • Support for shared nothing architecture
  • Steep learning curve
Scenarios where appropriate:
  • Heavy investment in other Oracle databases
  • Availability of knowledgable Oracle staff
  • Plenty of money for the database and all the add ons
  • Need for well supported platform
  • Data sets that are not ridiculously big. Once you start hitting table sizes in the hundreds of gigs, it starts getting very hard to scale
Scenarios where not appropriate:
  • Limited budget
  • Desire to use open source software
  • HUGE datasets. Until the architecture can operate in a shared nothing fashion, it will only scale to the size of the biggest box you can get. Even that may not be enough...
  • Lots of semi/unstructured data
  • Staff has limited knowledge on tuning it
Score 9 out of 10
Vetted Review
Verified User
Review Source
My organization designs, builds and maintains a data warehouse for various clients both from public and private sectors. Based on the individual client needs the data warehouse is being used both at the department level and as well as at the entire organization level. The data warehouse is being used to answer and provide insights to the organizations' various activities. Using the data warehouse the organizations are able to derive advanced analytic analysis and in turn increase fraud detection, efficiency and much more.
  • Able to handle very large data sizes efficiently from a performance, high availability and manageability perspective. This is accomplished through the Oracle Partitioning functionality. Partitioning allows large segments (tables, IOT index-organized tables, indexes) to be broken into smaller segments at the physical layer but treated as a whole at the logical layer.
  • Provides support for dual-format architecture through Oracle In-Memory functionality. Without any change to application code one can obtain in-memory performance. This functionality enables us to have the tables represented in both the row format and the column format using in-memory format. This is a huge boost for BI/analytic queries since the Oracle optimizer is able to intelligently choose the appropriate format.
  • Provision to materialize a subset of table data or table joins. This is through materialized views and the optimizer will rewrite the query against the base tables to make use of this materialized view. This provides a huge performance boost and is critical in VLDBs as in a data warehouse. The query rewrite is fully transparent to users.
  • Provides multiple compression capabilities. This is very useful not only for deducing the storage foot print but as well as increase performance at different layers of the infrastructure including query performance. The compression functionality can be applied against both structured and unstructured data.
  • With the advent of Engineered Systems (Exadata, Database Machine, SuperCluster) there are specific features and functionalities that can further boost the Oracle data warehouse. These are related to consolidation, Smart Scan, Storage Indexes, EHCC (Exadata hybrid columnar compression) and much more.
  • RAC - Real Application Clusters (with 2 or more nodes) provides functionality for high availability, performance and scaling as the work load increases. The parallelism is provided both within a node and as well as across nodes. If for any reason a node goes down the data warehouse is still available through other nodes and the running queries are transparently failed over to the surviving nodes.
  • For the query rewrite related to the materialized views the optimizer at times goes against the base tables. There is room for improvement for the optimizer to make more intelligent choices. There does exist functionality to identify the reason why the optimizer failed to do the rewrite of the original query. This can be further expanded.
  • On the storage indexes currently there is limitation of only 8 columns. In addition Oracle decides which of the columns are chosen as part of the storage index. It would be nice to see if both of these are addressed in future versions/releases.
  • Some of the features are 'Options' which would increase the overall licensing cost and is an important factor for certain class of users/clients. It would be nice to see if at least some of the options are standard functionality.
Oracle Data Warehouse is well suited for VLDBs (very large databases) and has core functionality to provide scalability and performance with data growth and as well user query load. It does provide the necessary features and functionalities for BI analytics, data consolidation, fraud analysis and detection. With Engineered Systems one can bring in database consolidation, shared flash storage, InfiniBand connectivity and much more into play. With the newer version, the multi-tenant architecture option is available. With multi-tenant, the user is now able to manage many databases as one with the use of Container and Pluggable databases.