As we made the transition to the cloud, Qubole’s ability to automate the infrastructure and automatically scale to meet the demands of our users saved us time, resources and budget.
SVP – Engineering & Operations, Wikia
Wikia is the ultimate hub for passionate pop culture fans around the world. As a digital media company with over 190 million global monthly visitors and over 360,000 fan communities, Wikia enables fans to come together and celebrate their passion for TV, movies, games and every pop culture topic imaginable. The company was founded in 2006 and is observing tremendous growth in not only the number of users and engagement, but also the amount of unstructured user data that can be used to improve the core product and user experiences.
The top challenge Wikia faced in its big data initiative was rapid scalability. Wikia has an extremely active user base that is growing exponentially and producing massive amounts of data. By analyzing it, the business has the ability to target users in specific communities in ways that would garner the maximum response and impact.
Previously, Wikia was using an on-premises Hadoop deployment based on Cloudera. However, as it scaled, Wikia realized it was going to have to grow it’s hardware footprint significantly and was unwilling to continue to make investments in a short term solution, and most of the company did not have easy access to the data. Data engineers are extremely hard to find and having them spend time on systems administration tasks was distracting them from their primary responsibilities, and without federated access to data to get both technical and non-technical users and analysts direct access to the platform, Wikia couldn’t deliver the insights needed to grow its business.
Rather than spending time and even more money further building out its rigid infrastructure, Wikia instead chose to invest in growing its team of data analysts and engineers while finding a cloud alternative to run its Hadoop clusters. Wikia was already using S3 to backup data for disaster recovery, and it wanted to add an analytics platform to take advantage of the data already hosted in S3.
Wikia selected Qubole as its analytics platform and migrated its on-premises clusters to Amazon Web Service (AWS). Wikia was able to fully migrate its big data infrastructure and workloads in a few months and has completely eliminated the overhead needed to manage its data platform.
Due to advanced automation and optimizations possible with the Qubole Data Service (QDS), Wikia was able to provide federated access to data and business critical intelligence across a large percentage of its workforce. Thanks to on-demand scaling leveraging AWS cloud resources and Qubole’s capability to auto-scale up or down dynamically in order to maintain the right cluster size to handle the workload, Wikia is able to spin up and grow capacity much easier than the on-premises tools it had used previously.
Moving to a software-as-a-service offering eliminated worries about versioning and ongoing maintenance. Wikia is able to receive updates about its analytics instantly and get detailed, in-depth support when needed. Analytics efficiency also improved dramatically because Wikia is able to co-locate its Hadoop processing and reporting with data storage on AWS using the many cloud optimizations available with QDS.
Thanks to Qubole’s ability to work across a shared Hive metastore, Wikia has migrated its workflows to the cloud while maintaining the uptime they need. Wikia is also able to easily and quickly test new data engines as they constantly seek to maintain its competitive advantage as a data-driven organization.
Qubole is a significantly more polished product than EMR. Data scientists can explore their data in S3, create tables and query those tables all via an easy-to-use web UI
Qubole’s fantastic support has been key in our successful deployment. They continue to deliver of new features and revisit the ones that we ask for
Our goal at MediaMath was to take our existing industry leading infrastructure to the next level handling new complex analytics tasks. Qubole has helped us enable this goal with minimal risk.
Instead of worrying about provisioning clusters of machines or job flows or whatever, Qubole lets you focus on your data and your queries … The Qubole guys have been extremely helpful!
The service spins up users’ clusters only when a job is started, then automatically scales or contracts them based on the workload, and spins the servers down once the job is done.
Qubole’s Hadoop and Hive interfaces are vastly superior to the default CLIs, which scare business analysts and hinder meaningful analyses of the gaming logs that we collect. With Qubole, business analysts are self-sufficient in using a Big Data platform to meet their advanced analytic needs.
Online Gaming Company
top-performing technologies in the data industry are definitely taking aim at democratizing data tools and bringing the power of data to smaller businesses. This is a major change in the data industry, and Qubole Data Service is a great example
I’m very happy to be using Qubole in production. Qubole has saved me a lot of time, effort, and trouble in getting my data processing pipelines up and running. My data pipelines process Appnexus data in Amazon S3 which is then stored in Vertica. The engineering team understands the complexities and provided awesome support!
Real-time Ads Retargeting Startup
There’s a whole world of web companies, SMBs and other non-Facebooks or Yahoos that will want to use Hadoop but not want to run it in-house…offering a cloud service makes it easier for these users to get started with the platform and for Qubole to keep improving.
Qubole offers a big data ETL and exploration service through auto-scaling Hadoop clusters with a web user interface for data exploration and integration with various data sources. The service can do (nearly) everything EMR can do, and it goes further
Big Data Republic
Simba knows Big Data access. Qubole knows Big Data. Qubole’s founders authored Apache Hive, built key parts of the Hadoop eco-system and brought Apache HBase to Facebook
“The integration of Tableau and Qubole makes it faster and easier for our customers to operationalize Big Data…lowers the resource barriers to deriving the benefits of Big Data because customers can deploy our joint solution seamlessly and cost effectively.”