Likelihood to Recommend I find Qubole is well suited for getting started analyzing data in the cloud without being locked in to a specific cloud vendor's tooling other than the underlying filesystem. Since the data itself is not isolated to any Qubole cluster, it can be easily be collected back into a cloud-vendor's specific tools for further analysis, therefore I find it complementary to any offerings such as Amazon EMR or Google DataProc.
Read full review It is well organized. One can use it for the company's portfolio management. Various tasks can be done for managerial purposes. One can track the material from start to end product: for example, raw material, packing material & consumable material to formulated bulk and formulated drug product. This can help to manage spending as well as finding costing of the product.
Read full review Pros From a UI perspective, I find Qubole's closest comparison to Cloudera's HUE; it provides a one-stop shop for all data browsing and querying needs. Auto scaling groups and auto-terminating clusters provides cost savings for idle resources. Qubole fits itself well into the open-source data science market by providing a choice of tools that aren't tied to a specific cloud vendor. Read full review Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information. Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data. Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions. Read full review Cons Providing an open selection of all cloud provider instance types with no explanation as to their ideal use cases causes too much confusion for new users setting up a new cluster. For example, not everyone knows that Amazon's R or X-series models are memory optimized, while the C and M-series are for general computation. I would like to see more ETL tools provided other than DistCP that allow one to move data between Hadoop Filesystems. From the cluster administration side, onboarding of new users for large companies seems troublesome, especially when trying to create individual cluster per team within the company. Having the ability to debug and share code/queries between users of other teams / clusters should also be possible. Read full review Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change Lack of clarity on licensing is one major challenge Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4 Read full review Likelihood to Renew Personally, I have no issues using Amazon EMR with Hue and Zeppelin, for example, for data science and exploratory analysis. The benefits to using Qubole are that it offers additional tooling that may not be available in other cloud providers without manual installation and also offers auto-terminating instances and scaling groups.
Read full review At this moment we are not focusing on SAP, however would love to in the future. This is primarily because of our limited ability to generate more revenue to fund for SAP partnerships and products. Our initial tryst with SAP Partneredge open ecosystem didn't go as planned and we have shelved that for now. Hope we can revive in the future
Read full review Usability In addition to the points described in the previous parts of the review, I believe that as I gain more experience with the product over time, I will be able to better describe my experience with this tool. Meanwhile, I can confirm that the possibilities presented to my organization by the change to SAP HANA, at the moment, have been very important to evolve the analytical and strategic field towards a new path.
Read full review Support Rating One specific example of how the support for SAP HANA Cloud impacted us is in our efforts to troubleshoot and resolve technical issues. Whenever we encountered an issue or had a question, the support team was quick to respond and provided us with clear and actionable guidance. This helped us avoid downtime and keep our analytics operations running smoothly.
Read full review Implementation Rating Professional GIS people are some of the most risk-averse there are, and it's difficult to get them to move to HANA in one step. Start with small projects building to 80% use of HANA spatial over time.
Read full review Alternatives Considered Qubole was decided on by upper management rather than these competitive offerings. I find that
Databricks has a better Spark offering compared to Qubole's Zeppelin notebooks.
Read full review I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.
Read full review Scalability Limitation of training deliverable by organization
Read full review Return on Investment We like to say that Qubole has allowed for "data democratization", meaning that each team is responsible for their own set of tooling and use cases rather than being limited by versions established by products such as Hortonworks HDP or Cloudera CDH One negative impact is that users have over-provisioned clusters without realizing it, and end up paying for it. When setting up a new cluster, there are too many choices to pick from, and data scientists may not understand the instance types or hardware specs for the datasets they need to operate on. Read full review ROI has always been high in terms of the functionality that it offers and the security features it comes with. Managing large volumes of data in real-time is not an easy task, but it does it pretty well with faster data processing. Read full review ScreenShots