HPE Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform.
N/A
Oracle Autonomous Data Warehouse
Score 8.4 out of 10
N/A
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
Pricing
HPE Data Fabric
Oracle Autonomous Data Warehouse
Oracle Exadata
Editions & Modules
No answers on this topic
No answers on this topic
Database Server
$2.9032
Per Unit
Quarter Rack
$14.5162
Per Unit
Offerings
Pricing Offerings
HPE Data Fabric
Oracle Autonomous Data Warehouse
Oracle Exadata
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
—
—
—
More Pricing Information
Community Pulse
HPE Data Fabric
Oracle Autonomous Data Warehouse
Oracle Exadata
Considered Multiple Products
HPE Data Fabric
No answer on this topic
Oracle Autonomous Data Warehouse
Verified User
Engineer
Chose Oracle Autonomous Data Warehouse
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 …
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.
First, get the database on Oracle. If you are in an Oracle stack, it would be much better to use the Oracle products. If you are driving a Ferrari, you wouldn’t put a Mercedes engine in it. If you are writing a query, you cannot rely on other brands. Since I'm an architect, when I look for a product, I look for performance.
The installation is easy because it comes out-of-the-box and you just start using it.
Previous to Oracle Exadata, we were using a normal Oracle RAC service. We were just waiting for this product to come out.
I'm currently writing a data warehouse on Exadata. Before this solution, we were aiming for this to be completed by 8 a.m., when our ETLs would finish. With the help of Exadata's special features, this was reduced to 3 a.m. This solution allows us to bring more data within the same time period. It provides us with more subject areas that provide more reports to our users. Our ETL times reduced to 65%, then to 50%.
MapR had very fast I/O throughput. The write speed was several times faster than what we could achieve with the other Hadoop vendors (Cloudera and Hortonworks). This is because MapR does not use HDFS, which is essentially a "meta filesystem". HDFS is built on top of the filesystem provided by the OS. MapR has their filesystem called MapR-FS, which is a true filesystem and accesses the raw disk drives.
The MapR filesystem is very easy to integrate with other Linux filesystems. When working with HDFS from Apache Hadoop, you usually have to use either the HDFS API or various Hadoop/HDFS command line utilities to interact with HDFS. You cannot use command line utilities native to the host operation system, which is usually Linux. At least, it is not easily done without setting up NFS, gateways, etc. With MapR-FS, you can mount the filesystem within Linux and use the standard Unix commands to manipulate files.
The HBase distribution provided by MapR is very similar to the Apache HBase distribution. Cloudera and Hortonworks add GUIs and other various tools on top of their HBase distributions. The MapR HBase distribution is very similar to the Apache distribution, which is nice if you are more accustomed to using Apache HBase.
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.
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.
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.
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.
Increased employee efficiency for sure. Our clients have various levels of expertise in their deployment and user teams, and we never receive complaints about MapR.
MapR is used by one of our financial services clients who uses it for fraud detection and user pattern analysis. They are able to turn around data much faster than they previously had with in-house applications
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.
