Cloudera Enterprise Data Hub vs. OpenText Vertica

Cloudera is critical for constructing an organizational data center
while maximizing the value of that volume of data.



Cloudera is great for comprehending data and querying for valuable
replies.



Cloudera supports data transfer from a variety of external databases and
third-party platforms.

Incentivized

As someone just starting out with data analytics and warehousing vertica is a great tool for a small scale business. It has amazing performance and can scale upto TBs of data. It works well for any organization which has about 100 - 500 DAUs of the system. The system doesn't require a lot of ops overhead. Scaling for PB data and 1000s of DAU is vertica's weak point. The system is just not designed for large scale usage and still has a long way to go to improve scalability. There are experiments to run Vertica query engine on top of HDFS which seem promising, however - if you have the the Hadoop ecosystem you are better off going the HDFS + Presto/Impala/SparkSQL route. But if you are in the Hadoop ecosystem, you probably are already investing a lot in ops.

Incentivized

• One of the oldest distributors of enterprise standard Hadoop.
• Distribution is based on open source Hadoop even though customizations are done on top of that.
• Faster updates and bug fixes to the products as they have Apache committers.
• Central configuration and control of your Hadoop platform (but still needs improvements).

Incentivized

• Column-oriented storage organization, which increases performance of queries.
• Compression, which reduces storage costs and I/O bandwidth. High compression is possible because columns of homogeneous datatypes are stored together and because updates to the main store are batched.
• Shared nothing architecture, which reduces system contention for shared resources and allows gradual degradation of performance in the face of hardware failure.
• Easy to use and maintain through automated data replication, server recovery, query optimization, and storage optimization.
• Support for standard programming interfaces ODBC, JDBC, ADO.NET, and OLEDB.
• Integration to Hadoop with the capability to perform analytics on ORC and Parquet files directly.

Incentivized

• Not fully Open Source, couple of components of the distributions are privately owned, meaning with public contributions are not welcome
• Improvements to Cloudera manager can only be recommended. its very hard to get it done once recommended as the full control is with them.
• Should make components more aligned to Open Source rather than making it closed sourced.
• Custom Features of open source software tools supported only by Cloudera are tricky. Cant commit changes to tools like Hue.
• Improvements to Cluster Management tool is required, which are already available to its competitors.

Incentivized

• One time, one of the nodes wasn't coming up because of some ambiguity with the local data. Vertica wasn't able to fix it by itself and we were trying to remove the node out of the database and we couldn't do it. It would be great if that could be addressed. Luckily when we rebooted the whole server, some of the dead transaction got flushed because of which vertica was able to recover and the node came up.

Incentivized

Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.

HP/Micro Focus Vertica support is in par with other bigger vendors. In addition to this, there is enough best practices documentation available for some of the most common ways you will use Vertica that makes it easy to get Vertica up and running.

Incentivized

Cloudera is a
great choice because it provides fast streaming data for tracking, breaks down
silos by providing unified self-service platforms for data-driven insights,
secures machine learning, AI solutions, and stores self-service data, enabling
our analysts to concentrate on more important tasks like displaying critical
information.

Incentivized

MySQL and MS SQL Server are both fantastic RDBMS products. MS SQL Server goes a bit further since it has the builtin analytical functions. But it only scales so far. Once the data goes beyond capacity, getting results out just does not happen anymore. IBM Netezza and Teradata were both appliances that required different expertise than we had in house. Vertica was able to do the same, and in some cases better, on commodity hardware (frankly in our case old servers that were slated for recycling!) and at a small scale. In other words, Vertica we could grow slowly over time. Infobright is a great log processing database but for the functions we were looking to serve it just didn't have some of the features Vertica had that we felt were show stoppers.

Incentivized

• Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
• Cloudera is definitely faster as wait time is reduced if on Cloud.
• A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.

• Vertica increased our productivity in analyzing the data and validating simple proof of concepts with our data.
• Results of analytical queries produced from Vertica are used by all departments as well as part of some of our products.

Incentivized