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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PostgreSQL
Score 8.5 out of 10
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PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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Oracle Autonomous Data Warehouse
PostgreSQL
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Oracle Autonomous Data Warehouse
PostgreSQL
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Community Pulse
Oracle Autonomous Data Warehouse
PostgreSQL
Considered Both Products
Oracle Autonomous Data Warehouse
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Chose Oracle Autonomous Data Warehouse
Reason to select Oracle Data Warehouse are mentioned below: 1. If some of your old process are already setup using Oracle Data Warehouse 2. High user community, which make solving doubt using internet very easy
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.
PostgreSQL, unlike other databases, is user-friendly and uses an open-source database. Ideal for relational databases, they can be accessed when speed and efficiency are required. It enables high-availability and disaster recovery replication from instance to instance. PostgreSQL can store data in a JSON format, including hashes, keys, and values. Multi-platform compatibility is also a big selling point. We could, however, use all the DBMS’s cores. While it works well in fast environments, it can be problematic in slower ones or cause multiple master replication.
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.
The stability it offers, its speed of response and its resource management is excellent even in complex database environments and with low-resource machines.
The large amount of resources it has in addition to the many own and third-party tools that are compatible that make productivity greatly increase.
The adaptability in various environments, whether distributed or not, [is a] complete set of configuration options which allows to greatly customize the work configuration according to the needs that are required.
The excellent handling of referential and transactional integrity, its internal security scheme, the ease with which we can create backups are some of the strengths that can be mentioned.
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 query syntax for JSON fields is unwieldy when you start getting into complex queries with many joins.
I wish there was a distinction (a flag) you could set for automated scripts vs working in the psql CLI, which would provide an 'Are you sure you want to do X?' type prompt if your query is likely to affect more than a certain number of rows. Especially on updates/deletes. Setting the flag in the headless(scripted) flow would disable the prompt.
Better documentation around JSON and Array aggregation, with more examples of how the data is transformed.
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.
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.
But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
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
Postgres stacks up just [fine] along the other big players in the RDBMS world. It's very popular for a reason. It's very close to MySQL in terms of cost and features - I'd pick either solution and be just as happy. Compared to Oracle it is a MUCH cheaper solution that is just as usable.
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.
The user-role system has saved us tons of time and thus money. As I mentioned in the "Use Case" section, Postgres is not only used by engineering but also finance to measure how much to charge customers and customer support to debug customer issues. Sure, it's not easy for non-technical employees to psql in and view raw tables, but it has saved engineering hundreds of man-hours that would have had to be spent on building equivalent tools to serve finance or customer support.
It provides incredibly trustworthy storage for wherever customer data dumped in. In our 6 years of Postgres existence, we have not lost a byte of customer data due to Postgres messing up a transaction or during the multiple times the hard-drives failed (thanks to ACID compliance!).
This is less significant, but Postgres is also quite easy to manage (unless you are going above and beyond to squeeze out every last bit of performance). There's not much to configure, and the out of the box settings are quite sane. That has saved us engineers lots of time that would have gone into Postgres administration.
