Compare Apache Hadoop vs. Oracle Exadata

Apache Hadoop is ranked 4th in Data Warehouse with 7 reviews while Oracle Exadata is ranked 1st in Data Warehouse with 13 reviews. Apache Hadoop is rated 7.6, while Oracle Exadata is rated 8.6. The top reviewer of Apache Hadoop writes "We are able to ingest huge volumes/varieties of data, but it needs a data visualization tool and enhanced Ambari for management". On the other hand, the top reviewer of Oracle Exadata writes "Exadata can significantly improve performance but there's a learning curve in a few key areas". Apache Hadoop is most compared with Snowflake, Pivotal Greenplum and Oracle Exadata, whereas Oracle Exadata is most compared with Teradata, Netezza and Oracle Database Appliance. See our Apache Hadoop vs. Oracle Exadata report.
Cancel
You must select at least 2 products to compare!
Apache Hadoop Logo
11,979 views|10,438 comparisons
Oracle Exadata Logo
19,215 views|13,646 comparisons
Most Helpful Review
Find out what your peers are saying about Apache Hadoop vs. Oracle Exadata and other solutions. Updated: September 2019.
370,655 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
What comes with the standard setup is what we mostly use, but Ambari is the most important.The best thing about this solution is that it is very powerful and very cheap.The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics.Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing.Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges.Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done.Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect.High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization.

Read more »

The most valuable feature is that you have the same familiar environment of an Oracle database but with the additional performance you get from this architecture.Reduced the cost while providing the benefits of Exadata storage, like, HCC compression, high disk capacity, etc.The technical support team are real professionals. I admire their technical skills and supports. Their supports are really admirable.Our machine is used for our internal development of Oracle-based solutions, PoC benchmarking, and training/familiarization.

Read more »

Cons
In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency.The upgrade path should be improved because it is not as easy as it should be.We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it.I would like to see more direct integration of visualization applications.Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them.General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error.It needs better user interface (UI) functionalities.

Read more »

It's too expensive per terabyte. It's complex.They should have allowed SQL offloading with reduced cost.We had issues with system restoration.We would like an option of a hardware-only support solution, but Oracle currently does not provide this.

Read more »

Pricing and Cost Advice
This is a low cost and powerful solution.​There are no licensing costs involved, hence money is saved on the software infrastructure​.

Read more »

Companies with limited budget for high end technology can now afford the Exadata machine.The price is very high.I did note that Oracle does tend to internally oversize things especially if they want to fill up a budget, and hence third-party oversight is essential.

Read more »

report
Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.
370,655 professionals have used our research since 2012.
Ranking
4th
out of 30 in Data Warehouse
Views
11,979
Comparisons
10,438
Reviews
7
Average Words per Review
478
Avg. Rating
7.6
1st
out of 30 in Data Warehouse
Views
19,215
Comparisons
13,646
Reviews
12
Average Words per Review
487
Avg. Rating
8.8
Top Comparisons
Compared 31% of the time.
Compared 30% of the time.
Compared 13% of the time.
Compared 24% of the time.
Compared 16% of the time.
Learn
Apache
Oracle
Overview
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Oracle Exadata Database Machine is a modern framework, engineered to run databases and to scale out database servers.

The main benefit of Exadata is speed. It hosts operating systems, CPU memory, and hard drives. It runs all types of databases, including online transaction systems, processors and data warehouses, while solving poor performances of old database architecture.

The Oracle Exadata Database Machine features a simple and fast database storage system that protects and backs up your critical data. It accelerates data warehouse performance for faster access to business information. It is ideal for companies looking to build up their infrastructure from scratch.

For more information on Oracle Exadata Database Machine, visit Oracle.com

Offer
Learn more about Apache Hadoop
Learn more about Oracle Exadata
Sample Customers
Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab PayPal, EBS, Organic Food Retailer, Garmin, University of Minnesota, Major Semiconductor Company, Deutsche Bank, Starwood, Ziraat Bank, SK Telecom, and P&G.
Top Industries
VISITORS READING REVIEWS
Software R&D Company28%
Financial Services Firm20%
Comms Service Provider12%
Government7%
REVIEWERS
Financial Services Firm21%
Comms Service Provider16%
Insurance Company16%
Retailer11%
VISITORS READING REVIEWS
Software R&D Company38%
Financial Services Firm14%
Comms Service Provider7%
Media Company6%
Find out what your peers are saying about Apache Hadoop vs. Oracle Exadata and other solutions. Updated: September 2019.
370,655 professionals have used our research since 2012.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
Sign Up with Email