200X Acceleration at
1/10th of the cost
Zero
maintenance
No credit card
required
Zero coding
infrastructure
Multi-level
security
Simplify HPCC System integration in
4 simple steps
Create connections
between HPCC System and targets.
Prepare pipeline
between HPCC System and targets by selecting tables in bulk.
Create a workflow
and schedule it to kickstart the migration.
Share your data
with third-party platforms over API Hub
Why choose Lyftrondata for HPCC System Integration?
Simplicity
Build your HPCC System pipeline and experience unparalleled data performance with zero training.
Robust Security
Load your HPCC System data to targets with end-to-end encryption and security.
Accelerated ROI
Rely on the cost-effective environment to ensure your drive maximum ROI.
Customer's Metrics
Track the engagement of your customers across different channels like email, website, chat, and more.
Improved Productivity
Measure the performance of your team and highlight areas of improvement.
360-degree Customer View
Join different data touch points and deliver personalized customer experience.
Hassle-free HPCC System integration to the platforms of your choice
Migrate your HPCC System data to the leading cloud data warehouses, BI tools, databases or Machine Learning platforms without writing any code.
Your Cloud Data Warehouses
Your BI Tools
Your Database
Your Machine Learning Tools
Hear how Lyftrondata helped accelerate the data journey of our customers
FAQs
What is HPCC System?
HPCC Systems (High-Performance Computing Cluster) is an open-source, data-intensive computing platform designed by LexisNexis Risk Solutions for big data processing and analytics. It provides a highly scalable, high-performance computing environment to handle massive datasets, making it a competitor to Hadoop and other big data frameworks.
What are the features of HPCC System?
High scalability:
HPCC can scale horizontally across many nodes in a cluster, allowing it to manage large volumes of data efficiently.
Integrated platform:
Unlike Hadoop, which requires several components (e.g., HDFS, MapReduce, Hive, etc.), HPCC Systems integrates data processing, storage, and delivery in one cohesive platform, simplifying its architecture and operations.
Data Parallelism:
The system efficiently handles data parallelism, meaning it processes chunks of data in parallel across different nodes to speed up performance.
What are the shortcomings of HPCC System?
Complexity of ECL:
Learning Curve: ECL (Enterprise Control Language) can be complex and has a steep learning curve for new users. Unlike SQL, which is widely known, ECL is specific to HPCC Systems and requires dedicated training and experience.
Limited Community Resources: Compared to more mainstream languages like SQL or Python, there are fewer resources and community support available for learning and troubleshooting ECL.
Integration and Ecosystem:
Ecosystem Limitations: Although HPCC Systems provides robust data processing capabilities, its ecosystem and integration with other big data tools and platforms can be less extensive compared to other systems like Apache Hadoop or Spark.
Limited Third-Party Integration: Integration with third-party tools and services may not be as seamless or well-supported as other platforms, potentially requiring custom solutions.
Real-Time processing constraints:
Latency: Despite the Roxie cluster’s capabilities for real-time processing, there might still be latency issues for highly interactive or time-sensitive queries compared to specialized real-time processing systems.
Deployment and maintenance:
Complex Deployment: Setting up and maintaining an HPCC Systems cluster can be complex, requiring expertise in both the platform and underlying hardware.
Management Overhead: Managing and scaling HPCC Systems clusters can involve significant overhead, including monitoring, tuning, and troubleshooting.
Make smarter decisions and grow your sales with Lyftrondata HPCC System integration
