Anonymous UserCo-Founder at a tech services company
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"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."
"The best thing about this solution is that it is very powerful and very cheap."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"It's good for storing historical data and handling analytics on a huge amount of data."
"The most valuable feature is the database."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"Scaling this solution is easy and the uptime is okay."
"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."
"The initial setup was really easy and straightforward."
"The MPP (Massively Parallel Processing) architecture helps to make things a lot faster."
"The most valuable feature is the scalability."
"The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range."
"The features we've found most valuable for data warehouses is extracting data, SSIS packages, and the DBs."
"Azure elasticity allows us to scale as much as we want, and it is pay-as-you-go, so we can scale up as we need to."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"The upgrade path should be improved because it is not as easy as it should be."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"It would be good to have more advanced analytics tools."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."
"I would like to see better integration with Active Directory, because we have had problems, and we still do."
"The initial setup process needs improvement. When you're moving to the cloud it takes a bit of time. It would be great if they could implement something that would make it faster."
"It would be of interest to improve things like the web service integration and availability in terms of being easy to create internal web services in the database."
"This is a young product in transition to the cloud and it needs more work before it is both settled as a product and competitive in the market."
"It's pay as you go, so you never know what your bill is going to be beforehand, and that's scary for customers. If you have someone who makes a mistake and the program's a loop that is running all night, you could receive a very expensive bill."
"With respect to what needs to be improved, concurrent connectivity has some limitations."
"I'm not entirely happy with the billing model. I'm not entirely happy with how the enterprise services are pretty expensive, but that's about it."
"The configuration for things like high-availability could be more user-friendly for non-technical users."
"This is a low cost and powerful solution."
"The price of this solution could be improved."
"The pricing is okay. You can pay as you go."
"This solution starts at €1000.00 a month for just the basics and can go up to €300,000.00 per month for the fastest version."
"When we are not using this solution we can simply shut it down saving us costs, which is a nice advantage."
"The licensing fees for this solution are on a pay-per-use basis, and not very expensive."
"All of the prices are available online."
"Our license is very expensive"
"They are cost aggressive, and it integrates well with other Microsoft tools."
Azure SQL Data Warehouse is a Fast, flexible, and secure analytics platform for the enterprise. Azure SQL Data Warehouse lets you independently scale compute and storage, while pausing and resuming your data warehouse within minutes through a massively parallel processing architecture designed for the cloud. Seamlessly create your hub for analytics along with native connectivity with data integration and visualization services, all while using your existing SQL and BI skills.
Apache Hadoop is ranked 3rd in Data Warehouse with 10 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 34 reviews. Apache Hadoop is rated 7.8, while Microsoft Azure Synapse Analytics is rated 8.0. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "Scalable, intuitive, facilitates compliance and keeping your data secure". Apache Hadoop is most compared with Snowflake, VMware Tanzu Greenplum, Oracle Exadata, Vertica and Teradata, whereas Microsoft Azure Synapse Analytics is most compared with Snowflake, Amazon Redshift, SAP BW4HANA, Oracle Autonomous Data Warehouse and Microsoft Parallel Data Warehouse.
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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.