Hadoop is a large-scale distributed batch processing infrastructure. While it can be used on a single machine, its true power lies in its ability to scale to hundreds or thousands of computers, each with several processor cores. Hadoop is also designed to efficiently distribute large amounts of work across a set of machines.
And it proved that the Hadoop solves the Big Data problems like Volume, Variety, Velocity and Values but we left with top 12 Hadoop challenges.
Hadoop is a complex distributed system with low-level APIs
Specialized skills are required for using Hadoop, preventing most developers from effectively building solutions
Business logic and infrastructure APIs have no clear separation, burdening app developers
Automated testing of end-to-end solutions is impractical or impossible
Hadoop is a diverse collection of many open source projects
Understanding multiple technologies and hand-coding integration between them
Significant effort is wasted on simple tasks like data ingestions and ETL
Moving from proof-of-concept to production is difficult and can take months or quarters
Hadoop is more than just offline storage and batch analytics
Different processing paradigms require data to be stored in specific ways
Real-time and batch ingestion requires deeply integrating several components
Common data patterns often require but don’t support data consistency and correctness
Cask – The Cask Data Application Platform (CDAP) is an open source, integrated platform for developers and organizations to build, deploy, and manage hadoop big data applications.
Bedrock – To realize value from an enterprise data lake and the powerful, but ever-changing ecosystem of Hadoop, you need enterprise-grade data management. Zaloni’s Bedrock is the industry’s only fully integrated Hadoop data management platform. By simplifying and automating common data management you can focus your time and resources on building the insights and analytics that drive your business. Bedrock makes it easy.
Mica - Historically data transformation has been an IT function where business analysts provide their requirements and IT builds and executes the transformation. Today enterprises want to modernize their Big Data architecture and shorten data preparation time so that data scientists and business analysts can be more productive. Mica provides the on-ramp for self-service data discovery, curation, and governance. You can evolve your capability to empower practitioners – from line of business end-users to highly skilled data scientists.
hTrunk – The product is built from ground to sophisticate Hadoop application development without having to write or maintain complicated Apache Hadoop code. To Meet the Enterprise needs by tackling the challenges of big data application development. hTRUNK provides a suite of components to deliver lower cost, higher capacity infrastructure.
Pentaho – A Comprehensive Data Integration and Business Analytics Platform. Within a single platform, our solution provides big data analytics tools to extract prepare and blend your data, plus the visualizations and analytics that will change the way you run your business. Regardless of data source, analytic requirement or deployment environment, Pentaho allows you to turn big data into big insights.
Talend - Talend simplifies the integration of big data so you can respond to business demands without having to write or maintain complicated Big Data code. Enable existing developers to start working with Apache Hadoop, Apache Spark, Spark Streaming and NoSQL databases today, in one platform. Use simple, graphical tools and wizards to generate native code that leverages the full power of big data and accelerates your path to informed decisions.
Informatica Big Data Management - Ingest, process, clean, govern, and secure big data to repeatable deliver trusted information for big data and analytics. And get access to an extensive library of prebuilt transformation capabilities on Hadoop using a visual development environment.
As always feel free to add in the list of software’s which can help enterprise to realize the power of Hadoop.