We performed a comparison between Apache Hadoop and SAP IQ based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R."
"The best thing about this solution is that it is very powerful and very cheap."
"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."
"It's open-source, so it's very cost-effective."
"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."
"The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."
"The performance is pretty good."
"The primary benefit of SAP IQ is its ability to limit the expansion of the costly SAP HANA database, which has limited storage capacity. This necessitates a form of data management that involves moving data from SAP HANA to SAP NLS, which is essentially archiving. This allows us to retain access to the data via a link whenever it is required."
"Valuable features for us include the compression, speed, fast response time, and easy object maintenance."
"Unbeatable speed and compression with a colummn-structured relational database."
"Columnar storage allows high compression, high load rates and high query performance."
"The column-based technologies (basically all the database for ITP) are used for SAP IQ. It is used as a column-based solution."
"It is very robust for ad hoc DW queries and its columnar compression is unique and valuable."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"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."
"The stability of the solution needs improvement."
"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 integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"I think the universe should be part of the Sybase IQ tool set."
"Multiplex is very problematic. There are consistency problems in the metadata, meaning it is possible to lose metadata consistency. You should make sure you have healthy backups."
"The solution works best when combined with other SAP solutions. If the environment has other systems other options might be better."
"The organization who owns the product does not support it well and appears not to be doing significant development for the future."
"The room for improvement would be the marketing of the product, because this product is much better than advertised."
"Concurrency and functional error messaging."
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while SAP IQ is ranked 16th in Data Warehouse with 17 reviews. Apache Hadoop is rated 7.8, while SAP IQ is rated 8.0. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". On the other hand, the top reviewer of SAP IQ writes "Easy to use, highly stable, but integration could improve". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas SAP IQ is most compared with Snowflake, SAP HANA, SQL Server, SAP BW4HANA and SAP Adaptive Server Enterprise. See our Apache Hadoop vs. SAP IQ report.
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