What is Hadoop?
Apache Hadoop is an open-source software platform. It is used for the distributed storage as well as the distributed processing of massive high-volume data sets on computer clusters created from commodity hardware.
Hadoop services allow for data storage, processing, access, governance, security, and operations. It is a common platform used by many businesses.
One of the reasons companies will use Hadoop is due to the platform’s ability to store and manage massive amounts of structured and unstructured data in a timely manner, and also reliably and for a low cost.
What Are The Big Benefits Of Hadoop
There are a handful of big benefits to Hadoop:
- Extensive flexibility. Unlike more traditional relational database management platforms, users will not have to create structured schemas before storing the necessary data. Users can store any data in any format of their choosing, and that includes partially structured or completely unstructured formats. Users can then parse and apply schema to the data when it is being read.
- Inexpensive for a majority of businesses. Proprietary software licenses or SaaS solutions can be pricey., Hadoop is open-source, like many of Apache’s product, and runs efficiently on cheaper commodity hardware.
- Excellent scalability and fast performance. The distributed processing of data to each node in a cluster lets Hadoop store, manage, implement, and analyze data at a massive scale.
- Reliable. Hefty computing clusters tend to succumb to failure of individual nodes in a cluster. Hadoop is known for being especially resilient. When a node inevitably fails, the processing function is redirected to the other nodes in the cluster. Data is then automatically replicated once more in preparation for additional node failures that could happen in the future.
When Hadoop is Not the Ideal Solution
On a basic summary level, Apache Hadoop is not the right solution (at least as a primary data source) when you intend to embed dashboards and reports from a business intelligence (BI) tool into your final software product. There are numerous reasons for this.
In order to build a very fast and very usable BI dashboard, especially one that can let you access the data you need on the spot with almost real-time latency, you will need a secondary software layer that can query all of your data.
When it comes to building up query acceleration, many businesses will use different SQL-layered-with-Hadoop solutions. These include solutions such as Hive or Apache Impala. These solutions are used in order to allow Structured Query Language (SQL) queries on Hadoop, but they end up not being speedy or flexible enough for particular resource-heavy requirements found in business intelligence.
Even though SQL is the main and most common query language used by data analysts around the world, Apache Hadoop still does not support SQL fresh from the box. SQL allows for connectivity and integration with business intelligence solutions.
However, an additional software layer such as Apache Hive in addition to an acceleration engine is usually needed to allow for proper business intelligence performance. Some business will start off in their early stages using SQL tech, but many businesses eventually come to the decision that SQL-layered-with-Hadoop solutions by themselves are not nearly enough to meet their specific use cases, regardless of industry. It just doesn’t work that well.
Data security will also to be addressed as well because out-of-the-box Hadoop implementations have notoriously bad security. In fact, many businesses are wary of keeping all of their sensitive data in just one location.
When it comes down to it, the main problem with using Hadoop for business intelligence solutions is that the act of communicating and converting data in Hadoop is extremely complex and tends to add latency, which inevitably slows down the report.
Embedding dashboards and reports for your end users need to be a speedy process within your applications. The only real solution that many businesses have found is to bring your Apache Hadoop data back into a database that is SQL-based for reporting purposes. This isn’t ideal for many business intelligence specialists.
Before jumping on the Hadoop bandwagon, make sure that your business is addressing the technology it has and the technology Hadoop is made for. It’s also vital to examine your organizational Enterprise Information Management (EIM) to see if Hadoop is even possible.
How Can Yurbi Help With Embedded Hadoop Reports?
Well beyond the cost savings that Yurbi can provide compared to most embedded BI vendors, there are a few ways that Yurbi can help with Hadoop.
First, we can connect via ODBC to Hadoop just like any other vendor in the BI space. But there are a few key features of Yurbi that can help solve the security and potential latency issues. Yurbi provide FastCache or in-memory dashboards. So instead of displaying real-time data on the first embed to your users, your dashboard could be run behind the scenes on a cache schedule, and not query Hadoop on the first render. When users want to drill down or change filters, Yurbi will query Hadoop to get the latest and real-time data.
Yurbi also has very robust data-level and multi-tenant security. So as we are pulling the data from Hadoop, the Yurbi App (semantic layer) makes it possible to uniquely provide end users only the data they should have access to. This applies to builders and viewers.
A second large benefit of Yurbi is that Yurbi is on-premise, self-hosted BI. Instead of other cloud services which would require you to extract the Hadoop data into their 3rd party, external cloud, with Yurbi everything stays on your local and secured network. Not only does this eliminate many security and privacy compliance concerns, it also speeds up the latency issue by having everything local.
Our Recommendations
Our main recommendation is to flatten out the Hadoop data you want to provide from a reporting perspective into a relational database. You get the power of ad hoc queries and the power of database views. But as we discussed above, you don’t have to, Yurbi can still provide white label, embedded dashboards and reports seamlessly integrated into your project.
Our next recommendation is to try Yurbi. We offer a full featured trial, and we encourage our evaluators to install Yurbi, connect it and let’s evaluate the performance for your requirements. It won’t take long to see quickly if Yurbi is the right solution or not ideal.
And our final recommendation, let’s start it off with a discussion. Schedule a live demo of Yurbi with one of our technical experts (not a sales call) and let’s discuss your plans and see how Yurbi can help be a part of them.
Are you pro-Hadoop for business intelligence solutions, or are you not so sure about it? Tell us about your experience with this platform in the comments section.