You are using an outdated browser. For a faster, safer browsing experience, upgrade for free today.
Hadoop Consulting and Support Services

Providing data analytics services since 2014, we understand analytical challenges that our customers face and know how to solve them, including the trickiest big data issues. Qrapp's consultants have been designing and implementing big data solutions since 2014. Our developers focus on Apache Hadoop as one of the pioneering frameworks, but our expertise goes far beyond it. In our projects, we also use such big data technologies as Apache Hive, Apache Spark and Apache Cassandra to offer the most efficient solution.

Hadoop Services We Render
Hadoop health check

Our big data consultants can explore your existing Hadoop clusters to find out whether there are any drawbacks or problems. You will get a detailed report on the status of your system, as well as suggestions on how to optimize it. For instance, some minor changes in the algorithms can lead to a substantial cost reduction or a system speedup.

Hadoop architecture design

If you need a solution from scratch, we plan every component carefully to ensure that your future system is in line with your business needs. We estimate your current and future data volume, as well as the required speed of the system to design the architecture accordingly. Applying a comprehensive approach, we do not limit the technology stack with Apache Hadoop, but offer a combination of frameworks and technologies to get maximum performance.

Hadoop implementation

Our experienced big data practitioners will bring to life the project of any complexity. Be sure that you will get our professional advice about whether to deploy the solution on premises or in the cloud. We will help you calculate the required size and structure of Hadoop clusters. We install and tune all the required frameworks, making them work seamlessly, as well as configure the software and hardware. Our team sets up cluster management depending on the load to ensure great working efficiency and optimized costs.

Hadoop integration

Are you planning to use Hadoop Distributed File System as a storage platform and run analytics on Apache Spark? Or maybe you are considering HDFS as a data lake for your IoT big data and Apache Cassandra for a data warehouse? In any case, our team ensures Hadoop’s seamless integration with the existing or intended components of the enterprise system architecture.

Hadoop support

We will support your project at any stage whether it’s kick-off or post-implementation maintenance. With proper settings, replication and backup configurations, you won’t have to worry about data security.

If you are to migrate to a new environment (for example, to the latest framework version), our team will solve this challenge as well.

Challenges We Solve
New analytical needs should be satisfied fast

With 5 years of experience in data analytics and 5 years in big data, our team has enough expertise to deliver an analytical solution tailored to your business needs as quickly as possible. Our project portfolio includes projects of different complexity and in multiple industries. We are ready to design, implement and support a Hadoop solution to help you get maximum value out of your big data.

Excessive computing resource consumption

We will provide you with an end-to-end Hadoop-based solution. As a framework, Apache Hadoop does not require expensive tailored hardware to deal with large volumes of data – its concept of distributed storage and parallel data processing allows using standard affordable machines. Besides, while designing the architecture, we will select those technology options that will solve your business tasks in the most efficient way.

Growing need for real-time analytics

Hadoop Distributed File System is a good choice for data lakes, massively used for real-time big data analytics solutions. However, to build a solution that perfectly satisfies your need for real-time analytics, you should strengthen Hadoop with other big data frameworks. Depending on the solution’s architecture, this can be, for example, Apache Kafka that allows data streaming or Apache Spark that enables in-memory parallel processing and may be up to 100 times faster than MapReduce – Hadoop’s data processing framework.

Misconfigured Hadoop clusters

Our team can also help the companies that have misconfigured Hadoop clusters deployed by different vendors. We configure Hadoop clusters so that they are compatible and run smoothly.

Get Your Hadoop Consulting

Whether you are in need of expert advice on your existing Hadoop clusters or a seamless implementation from scratch – our team will be happy to help.

See us in action!

We’d love to stay in touch. Describe the digital challenge you’ve faced, and we’ll get back to you with a solution we can offer.