In a world where new big players rise above the competition by harnessing the power of data better than others, future-proof businesses can’t afford to be held back by traditional databases. For this, we surveyed leading data-driven companies last quarter about what they considered to be the biggest challenges to their current databases. To provide additional context, we also included companies that were able to overcome these challenges by employing an in-memory analytic database. So, without further ado, here are the answers:
Performance takes the first place, with 30% of participants identifying it as their biggest challenge. This might not come as a surprise to data-minded individuals, but it does cement the fact that a fast database is the key to achieving valuable insights with data analytics. And without in-memory, it’s just not possible to run analytic queries in real time.
Wooga, developer of blockbuster games like “diamond dash” agrees: “If you have the choice between waiting several hours for analytic queries to run or obtaining results immediately, the decision is easy. By using EXASOL, our analytics run faster by a factor of 80 to 100, depending on the nature and scope.”
Runner-up is fast growth of data volumes with 23% of participants signaling it as a challenge. Data sources and sizes are increasing rapidly – according to a Digital Universe study by IDC, global data volumes will reach 5 Zettabytes by 2020 – and our survey shows businesses are already feeling the heat. A database needs to be able to scale accordingly, because even the most impressive feature list will disappoint if it is overwhelmed by rising data volumes.
MyThings, a leading online marketing company confirms this: “Thanks to the optimal scalability of the database, we could upgrade our servers multiple times in just two months without incurring extra costs. Our system grew rapidly from four servers with a total of 288 GB of main memory to a cluster of six Dell servers with a total of 4.5 TB of memory. As a result, we can now run complex analysis workloads on more than 20 TB of raw data.”
Completing the top three, cost of operations follows with 19% of participants pointing to it as a big challenge for their database. IT managers are often restricted by tight budget planning, and aside from the acquisition and licensing costs, maintenance and administration overhead are added burdens that are frequently overlooked. For this reason, it is crucial that databases deliver a justifiable total cost of ownership (TCO) and a strong price-performance ratio.
Dailyme TV, developer of an app that enables watching television on wireless devices, both online and offline, concurs: “The installation, configuration and maintenance of a database management solution can be very time-consuming and can result in high costs. With indexes being created automatically on the fly in the database, we save ourselves a lot of work. As a result, we have been able to reduce the TCO of the solution significantly.”
Data quality was mentioned by 19% of those that completed the survey, but it is only of peripheral concern to a database, because inferior data quality does not come from the database itself but from factors outside of it. Although a well-designed database can alleviate some of the pains of bad data quality, it is up to the data analysts and data scientists to design a coherent concept of what data is to be analyzed in the database, and to ensure good data quality in the first place.
Trailing the other four answers, 9% chose support as one of their biggest challenges to their database. However, the advantages of good support are nevertheless substantial. People may tend to think they only need it when things go wrong, but comprehensive support can provide a platform that ensures such major problems won’t occur in the first place, and make it possible for businesses to concentrate on what’s important.
Wunderdata, an e-commerce and business intelligence specialist agrees: “Thanks to EXASOL, we can now put the focus squarely on our own business instead of worrying about scalability problems. A high performance, affordable database solution that offers low service-level costs is vital for startups that have limited budgets.”