The Current and Future State of Databases: Per Actian
The Current and Future State of Databases: Per Actian
Large enterprises are reaching the limits of their database appliances, and Big Data adopters are having problems with performance as data volumes scale.
Join the DZone community and get the full member experience.Join For Free
Built by the engineers behind Netezza and the technology behind Amazon Redshift, AnzoGraph™ is a native, Massively Parallel Processing (MPP) distributed Graph OLAP (GOLAP) database that executes queries more than 100x faster than other vendors.
How are you and your company involved in databases?
We are a data infrastructure provider as such we have a variety of databases and data integration technologies in our portfolio. Our databases run the gamut from an embedded SQL engine, through NoSQL and relational DBMS’s that support OLTP and analytics capabilities. I am responsible for the development and delivery of our relational database solutions which includes Ingres, Actian X and Vector which scale from a laptop through to the biggest Hadoop cluster.
What are the keys to a successful database strategy?
Speed is key if that speed advantage can drive new or additional business value. There are products currently on the market that provide real-time analytics on operational data. An example of where it can drive business value is to be able to report on inventory in real time and drive a just-in-time supply chain so money isn’t held up unnecessarily in inventory.
Executing on a database strategy that can scale is hugely important from a cost and performance perspective. As data volumes grow and the infrastructure supporting it needs to grow, it’s important that it doesn’t bankrupt the business. We’ve seen several instances where a database appliance strategy was adopted only to see the whole thing fall apart when the data volumes reached the capacity of the appliance. Bolting on additional capacity isn’t an option, so an expensive migration project ensues. This is massively costly and risky migration could have been avoided if the data growth rates and scale had been considered up front.
It’s also important to consider scale when designing applications that will be deployed against the database. Will user expectations remain unchanged as data volumes grow? Will a dashboard that took 5 seconds to render when run against 500GB of data, ever return when running against a petabyte? Planning for scale and factoring in data growth rates when designing applications is key.
Much of the world has woken up to the importance of data security via well-publicized data breaches like the Experian breach of last year that exposed hundreds of millions of social security numbers. GDPR, which has global applicability, is forcing the issue of securing PII data. I believe the procedures put in place to secure PII data will extend to non-PII data and that data security will become less important from a strategic perspective as it’ll be a part of the natural order.
How can companies benefit from databases?
Many organizations consider data to be their crown jewels. Being able to use that data to get a competitive edge over their peers is what differentiates successful companies. Some of the largest companies in the world are built entirely on their data platform e.g. Google, Facebook, LinkedIn, Salesforce.
Companies in other sectors also benefit greatly from data stored in a database. For instance, in the manufacturing vertical, historical data can be used to schedule predictive maintenance to avoid unplanned downtime and to minimize maintenance windows.
Financial services companies use data accumulated about a customer’s past usage patterns to identify and prevent fraud. Healthcare companies can use data that they collect to identify and control disease outbreaks before they become epidemic or pandemic.
How have databases changed in the past year?
There are two areas in which we have seen a massive spike in interest in the past year:
Supporting AI and ML workloads
Focus on security features and processes as a result of GDPR
What are the technical solutions you, or your clients, use for your databases?
Unruly Media was able to help advertisers engage global audiences through their video marketplace while using our vector solution to manage their data. We aid Unruly in their process of emotional testing and targeting, monitoring social video campaign data and real-time optimization to help leverage video data. With almost 2.2 million viewer reactions to videos, we enabled Unruly in providing a deep analysis of its business metrics to assist them with calculating its revenue from web traffic log data.
What are real-world problems you, or your clients, are solving with databases?
Expandium: Telecom Network Tools Provider
Company Background: Innovative provider of leading network monitoring solutions to manage global transportation and mobile systems
Challenge: Expandium’s customer (large telecommunications provider with more than 20 million users) needed to analyze service quality for more than 4 billion mobile calls and messages per day over 10 days. Traditional databases could not scale to allow them to drill down to individual calls.
Solution: Provided vector solution on Hadoop solution across 12 nodes working on 100TB+ of data. Scaled to provide analytics on transaction data for 20 million customers, and now manages 40 billion transactions covering 10 days
Benefits: Carrier is now able to manage service to meet SLA objectives and maintain customer satisfaction levels
Company Background: Kiabi is a French ready-to-wear distribution group with >1B Euros in Revenue
Challenge: Kaibi needed to do data mining, to collect more data and support predictive analytics on markdowns to improve marketing campaign conversions
Solution: We provided analytics on sales for 20 million customers across 800 million records
Benefits: Response times up to 200x faster than a legacy database with a 10x reduction in physical data size
TNT Express (now owned by FedEx): Transportation and Logistics
Company Background: One of the world’s largest express delivery companies. Circa 1m consignments per day, via road and air transportation. 2013 revenues were €6.7bn
Challenge: Multiple data feeds, data management and data loading into a data warehouse
Solution: We provided user configurable reporting framework incorporating flexible dashboarding using complimentary BI system
What are the most common issues you see companies having with databases?
We’re seeing a significant uptick in interest in migrating to our technologies from organizations that are seeing their infrastructure breaking down because it wasn’t designed to handle scale. Large banks are reaching the limits of their database appliances, and Big Data adopters are having problems with performance as data volumes scale.
Where do you think the biggest opportunities are in the evolution of databases?
I see many parallels between the disruption that’s happening with Hadoop and the big data world and Linux in the 1990’s. There is a demand for a big data solution built on commodity hardware and at a commodity price point. It’ll be interesting to see if products like Teradata, Exadata, Vertica etc. go the way of the proprietary Unixes.
What are your biggest concerns regarding databases today?
Being able to provide a single view of the business or the customer, incorporating all of the data assets and visualized in a single dashboard or report. The large database providers are focused on protecting their footprint in accounts and not on enabling this use case. We are uniquely focused on this problem because we cover the entire data ecosystem.
Opinions expressed by DZone contributors are their own.