We are a team of engineers with experience building big data solutions for organizations that have some of the world's largest information management systems.
Thousand Data Points
What We Do
We build Big Data Solutions
We build custom information management solutions for very
large datasets (Big Data) that when stored in traditional
database storage systems render them unsuitable for data
analyatics due to their slow performance.
Our solutions are fast, scalable, continuosly available, cost
effective and are powerful enough to be able to perform
different types of analytics such as predictive and behavior
Our solutions are cloudy ready and have been designed to take
advantage of distributed computing resources, where available.
This provides scalability as the amount of data and the number
of users grow.
We also provide the ability to geo-replicate the data across
cloud availability zones across the globe. This ensures
continuous availability in the event of a failure and also
allows the storage/retrieval of data from the closest
availabiliy from the source increasing transmission efficiency
and reducing latency.
As various cloud providers have availability zones in
different geographic regions. We, optionally, provide the
ability to replicate data between different cloud providers
creating a hybrid cloud system that provides coverage in regions
that provide the best latency and throughput for our
In order to address data security and privacy concerns we
also provide the ability to store data in encrypted form so that
data privacy is maintained even in the event of a data
How we are different
We love what we do
At Corelogiq, our focus is on developing solutions that are custom tailored for a specific problem based on an in-depth analysis of the nature of data involved.
Most big data solutions today are built by simply gluing together free or open source technologies and developing generic solutions. While such solutions work well in simple and low to medium sized applications they start to become expensive once size of data and users increase. The cost of hardware involved in horizontal scaling, data replication and bandwidth will grow rapidly making these solutions prohibitively expensive.
By getting a deeper understanding of the nature of the data involved and addressing the intricacies of storage, transmission and use of data, including analytics, we are able to develop solutions that are lightning fast, scale well and cost effective.