Tag Archives: hp

DBTA Webinar Review: Leveraging Big Data with Hadoop, NoSQL and RDBMS

A presentation last week, hosted by Database Trends and Applications (DBTA), was a great example of some interesting technical information presented poorly. As that sentence implies, this column is one about the marketing of business intelligence (BI), not about the technology – well, not much…

There were three presenters: Brian Bulkowski, CTO and Co-founder, Aerospike; Kevin Petrie, Senior Director and Technology Evangelist, Attunity; Reiner Kappenberger, Global Product Management, HPE Security – Data Security.


Brian was first at the podium. Aerospike is a company providing what they claim is a very high speed, scalable database, proudly advertising “NoSQL!” The problem they have is that they are one of many companies still confused about the difference between databases and SQL. A database is not the access method. What they’re really focused on in loosely structured data, the same way Hadoop and other newer databases are aimed. That doesn’t obviate the need to communicate via SQL.

He also said that the operational in-memory market is “owned by NoSQL.” However, there were no numbers. Standard RDBMS’s, columnar and NoSQL databases all are providing in-memory storage and processing. In fact, Information Management has a slide show of Gartner’s database analytics vendor report and you can see the breadth there. In addition, what I constantly hear (not statistically significant either…) is that Hadoop and other loosely-structured databases are still primarily for batch. However, as the slide show I just mentioned is in alphabetical order, and Aerospike is the first one you’ll see. Note again that I’m pointing out flaws in the marketing message, not the products. They could have a great in-memory solution, but that’s doesn’t mean NoSQL is the only NoSQL option.

The final key marketing issue is that he kept misusing “transactional.” He continued to talk about RDMS’s as transactional systems even while he talked about the power of Aerospike for better handling the transactions. In the later portion of his presentation, he was trying to say that RDBMS’s still had a place, but he was using the wrong term.


Attunity’s Kevin Petrie was second and his focus was on Attunity Replicate. The team of Aerospike and Attunity again shows the market isn’t yet mature enough to have ETL and databases come smoothly together. Kevin talked about their 35 sources and it seem that they are the front end in the marketing paring of the two companies. If you really need heterogeneous data sources and large database manipulation, you’ll need to look at the pair of companies.

My key issue with this section was one of enterprise priorities. Perhaps the one big, anonymous reference they both discussed drove the webinar, but it shouldn’t have owned the message. Mr. Petrie spent almost all his time talking about Hadoop, MongoDB and Kafka. Those are still bleeding edge tools while enterprise adoption requires a focus on integrating with standard and existing sources. Only at the end, his third anonymous case, did Kevin have a slide that mentioned RDBMS sources. If he wants to keep talking with people running experimental and leading edge tests of systems, that priority makes sense. If he wishes to talk to the larger enterprise market, he needs to turn things around.

The other issue was a slide that equated RDBMS, Data Warehouse and Hadoop as being on equal footing. There he shows a lack of business knowledge. The EDW, as an old TV would declare, is the one of these things that is not like the other. It has a very different purpose from the two database technologies and isn’t technology dependent.

HPE Security

Reiner Kappenberger gave a great presentation but it didn’t belong. It seems the smaller two firms were happy to get HP to help with the financing but they didn’t think about staying on message.

Let me make it very clear: Security is of critical importance. What Mr. Kappenberger had to say was very important for people to hear. However, it didn’t belong in this webinar. The topic didn’t fit and working to stuff three presenters into forty minutes is always tough. Another presentation where all three talked about how they work to ensure that the large volumes of data can be secure at multiple levels would have been great to hear – and I hope the three choose to create such a webinar.


This was two different webinars stuffed into one, blurring the message. In addition, Aerospike and Affinity either need to make sure they they’re not yet trying to address the mass market or they need to learn how to stop speaking to each other and other leading edge people and begin to better address the wider enterprise market.

The unnamed reference seemed to be a company that needed help with credit card transactions and fraud detection, and all three companies worked to provide a full solution. However, from a marketing standpoint I don’t think they did proper service to their project by this webinar.

Marketing lesson: How to cram too many vendors into too short a timeframe

I’ll start by being very clear: This is a slam on bad marketing. Do not take this column as a statement that the products have problems, as we didn’t see the products.

Database Trends and Application magazine/website held a webinar. The first clue there was something wrong is that an hour long seminar had three sponsors. In a roundtable forum, that could work, and the email mentioned it was a roundtable, but it wasn’t. Three companies, three sequential presentations. No roundtable.

It was titled “The Future of Big Data: Hybrid Architectures and Best-of-Breed”. The presenters were Reiner Kappenberger, Global Product Manager, HP Security Voltage, Emma McGrattan, SVP Engineering, Actian, and Ron Huizenga, ER/Studio Product Manager, Embarcadero. They are three interesting companies, but how would the presentations fit together?

They didn’t.

Each presenter had a few minutes to slam through a pitch, which they did with varying speeds and content. There was nothing tying them into a unified vision or strategy. That they all mentioned big data wasn’t enough and neither was the time allotted to hear significant value from any of them.

I’ll burn through each as the stand-alone presentations they were.

HP Security Voltage

Reiner Kappenberger talked about his company’s acquisition by HP earlier this year and the major renaming from Voltage Security to HP Security Voltage (yes, “major” was used tongue-in-cheek). Humor aside, this is an important acquisition for HP to fill out its portfolio.

Data security is a critical issue. Mr. Kappenberger gave a quick overview of the many levels of security needed, from disk encryption up to authentication management. The main feature focus on Reiner’s allotted time is partial tokenization, being able to encrypt parts of a full data field. For instance, disguising the first five digits of a US Social Security number while leaving the last four visible. While he also mentioned tying into Hadoop to track and encrypt data across clusters, time didn’t permit any details. For those using Hadoop for critical data, you need to find out more.

The case studies presented included a car company’s use of both live, Internet of Things feeds and recall tracking but, again, there just wasn’t enough time.


The next vendor was Actian, an analytics and business intelligence (BI) player based on Hadoop. Emma McGrattan felt rushed by the time limit and her presentation showed that. It would have been better to slow down and cover a little less. Or, well, more.

For all the verbage it was almost all fluff. “Disruption” was in the first couple of sentences. “The best,” “the fastest,” “the most,” and similar unsubstantiated phrases flowed like water. She showed an Actian built graph with product maturity and Hadoop strength on the two axis and, as if by magic, the only company in the upper right was Actian.

Unlike the presentations before and after hers, Ms. McGrattan’s was a pure sales pitch and did nothing to set a context. My understanding, from other places, is that Actian has a good product that people interested in Hadoop should evaluate, but seeing this presentation was too little said in too little time with too many words.

In Q&A, Emma McGrattan also made what I think is a mistake, one that I’ve heard many BI companies get away from in the last few years. An attendee asked about biggest concern when transitioning from EDW to Hadoop. The real response should be that Hadoop doesn’t replace the EDW. Hadoop extends the information architecture, it can even be used to put an EDW on open source, but EDWs and big data analytics typically have two different purposes. EDWs are for clean, trusted data that’s not as volatile, while big data is typically transaction oriented information that needs to be cleaned, analyzed and aggregated before it’s useful in and EDW. They are two tools in the BI toolbox. Unfortunately, Ms. McGrattan accepted the premise.


Mr. Huizenga, from Embarcadero, referred to evidence that the amount of data captured in business is doubling every 1.2 years and how the number of related jobs is also exploding. However, where most big data and Hadoop vendors would then talk about their technologies manipulating and analyzing the data, he started with a bigger issue: How do you begin to understand and model the information? After all, schema-on-write still means you need to understand the information enough to create schemas.

That led to a very smooth shift to a discussion about the concept of modeling to Embarcadero. They’ve added native support for Hive and MongoDB, they can detect embedded objects in those schemas and they can visually translate the Hadoop information into forms that enterprise IT folks are used to seeing, can understand and can add to their overall architecture models.

Big data doesn’t exist in a void, to be successful it must be integrated fully into the enterprise information architecture. For those folks already using ERwin and those who understand the need to document modeling, they are a tool that should be investigated for the world of Hadoop.


Three good companies were crammed into a tiny time slot with differing success. The title of the seminar suggested a tie that was stronger than was there. The makings existed for three good webinars, and I wish DBTA had done that. The three firms and the host could have communicated to create an overall message that integrated the three solutions, but they didn’t.

If you didn’t see the presentation, don’t bother. Whichever company interests you check it out. All three are interesting though it might have been hard to tell from this webinar.

HP Vertica at the BBBT: Technology v Solution

The latest BBBT presentation was from HP Vertica’s Will Cairns and Steve Sarsfield. I know it’s hard to miss HP’s presence in any market, but for those few of you who may have done so HP acquired Vertica in early 2011. Vertica is a columnar database focused on large data sources for analytics. Will and Steve were a good tag team, switching back and forth as need be; so unlike other presentation reviews I will rarely be noting who said what.

The smallest installation they mentioned runs on HP Vertica is 1.5 terabytes up to very large ones such as at Facebook, their largest customer. Without a doubt, HP plays at the larger end of the analytics market. They have a strong and powerful database and it seems HP’s hardware experience and Vertica’s database knowledge seems to have been integrated far better than other HP acquisitions in the previous decade.

The problem I often come back to discuss, whether talking about a startup or a company such as HP, is the issue of technical problems versus business solutions.

Will Cairns did say one thing that should be paid attention to by many who talk about unstructured data. His very accurate point is that “unstructured data doesn’t stay unstructured long.” We talk about conversations as unstructured, but to get information from those, we must part the syntax of sentences, look for key words and meaning, and extract semantics with meaning. Those items can then be similarly structured in order to compare, analyze and draw conclusions.

However, the weak spot in his eyes is his title. He constantly referred to “supporting data scientists” rather than supporting data science. As the programmers who know statistics create more and more packages that can analyze data, it’s the analytical capabilities being provided to business people that matters, not the people who call themselves data scientists who also just exist to serve the end business use.

One interesting techie note about their MPP database is that there isn’t an automatic lead node. While there’s no independent analysis for intelligence allocation of notes other than, it seems, basic load balancing, the idea that you can automatically define a lead node based on balancing, not before, does imply a good ability to manage distributed resources.

One thing I’ve asked a few folks who push columnar databases came up again in this presentation. They were talking about something called projections, which seemed to be ways to index the data for faster access. However, they claimed it’s not indexing but gave no clear explanation.

I then asked the question that always intrigues me. It’s clear that columnar databases have a great strength in analytics across records because indexes aren’t needed for columns, but it’s clear that both row and column based analyses have value, so getting a clearer picture how any database supports both would seem to be important. I pointed out that indexes in row-based databases exist to allow faster search of columns. The question is: What techniques are used to speed up row based searches in columnar databases if no indexes exist. They didn’t have an answer.

One slide that created a great conversation was one of the types of analytics and their definitions. Claudia Imhoff and others questioned the difference between predictive, prescriptive and pre-emptive analytics. While better clarity is definitely needed, the attempt is a great conversation starter for the industry.

HP Vertica - Hindsight to Foresight slide


HP Vertica seems to be a database that should be evaluated for large data volume analytics. However, they seem to have a focus on the technology not on why companies want the technology. There was no real discussion of results, or of partnerships with BI vendors to provide end user value. I expect that successful sales won’t be purely HP. They are focused purely on IT and programmers who are building very complex algorithms. They’ll need either a channel or ISV partner to round out the picture to an enterprise who needs to see the full business value chain.

It seems to be a very strong product, but only part of the solution.