Software Integration Maximizes Interoperability for Agritech Provider
Agriculture Industry │Systems Integration │UI/UX
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954 342 5676 
+44 137 243 2466
Let's Talk! 954 342 5676 +44 137 243 2466
We distribute large data sets across clusters of computers using Apache Hadoop’s framework and simple programming models. Gain better big data insights and improved flexibility, scalability, and cost-effectiveness with our Hadoop development services.
Chetu's Hadoop development boasts developers with experience in related technologies such as Spark, Scala, Python, Cloudera, Hive and Impala that enable the massive storing of data and running applications..
Our MapReduce framework implementation enables a significant volume of data on large clusters to be processed, as well as generates big data sets with a parallel, distributed algorithm.
Our Hadoop developers perform integration solutions with software components such as Hive, Pig, Flume, Ambari, HCatalog, Solr, Cassandra, Sqoop, Zookeeper, HBase, and Oozie.
Our Hadoop development solutions enable enterprises to gain better insights from data and achieve scalability, flexibility and cost-effectiveness.
Our developers utilize the Hadoop YARN (Yet Another Resource Negotiator) architecture that enables system resource allocation to applications operating in clusters while organizing tasks.
Our developers provide maintenance services for your critical business processes. Our developers provide improved functionality and lessen the need for continued maintenance.
We optimize your organizations performance with custom Hadoop development. We help IT departments balance current workloads with future storage and processing needs.
Our expert developers understand dynamic market trends, as well as how to create a smooth transition of your existing platforms and frameworks using Hadoop migration.
Our team of experienced software developers provides best-in-class Hadoop development and implementation services for big data solutions.
Our Hadoop experts will optimize your current Hadoop platform to add more personalized business requirements, relevant current trend feeds, and so much more.
Our team provides SAS/ACCESS to all of Hadoop’s features, including SAS statement mapping, query language support, seamless data access, metadata optimization, HIVE interface support, and more.
To help you make important, accurate decisions based on real-time information, we integrate real-time analytics modules.
Our Hadoop experts help businesses of all sizes and industry verticals create a strategy, implement, integrate, build, and test your custom solutions.
To effectively manage your data analytics, we offer data setups and data pipeline streaming that are highly comprehensive and easy to use.
Our developers leverage popular big data technologies, including Apache Hive, Apache Spark, Apache Cassandra, and so many more to provide you with high-performance, effective big data solutions.
We help companies bridge the gap between their ability to perform properly interpreted and reported analysis and the large volume of complex data by providing Big Data consulting and development services.
We offer custom HDFS (Hadoop Distributed File System) services, using different architectures, like NameNode and DataNode, to ensure that all file systems are distributed properly.
ELT data
Archiving
Big Data analytics
Pattern matching
Batch aggregation
Data warehousing
Cost-effective data
Data transformation
We provide a business toolkit for video service providers to improve customer engagement, marketing performance, content personalization, retention, and more to ramp up your ROI. JUMP's platform accumulates video service providers' backend and frontend data sources that are enriched through big data, artificial intelligence, and machine learning capabilities.
Our engineers create Hadoop solutions for large-scale data storage and seamless data processing.
To deliver data-enriched applications with a larger amount of datasets, we use Apache Drill.
Apache Zookeeper allows us to provide a key-value store that exists on a hierarchy.
We create SQL-like interfaces used to file systems for query data and other various databases by using Apache Hive.
Apache HBase, running on top of Alluxio, providing Bigtable capabilities for Hadoop as well.
Hadoop MapReduce is used to effectively distribute large sets of data computing and processing.
Apache Cassandra is an excellent tool used to program interfaces for data parallelism clusters and fault tolerance.
We use Apache YARN for interactive processing streaming and running data for batch processing.
To create scalable machine algorithms using Apache Mahout.
For optimizing your storage and Hadoop cluster access, we utilize HDFS’s DataNote and NameCode architectures.
We use Apache Solr for database integration, document handling, indexing, dynamic clustering faceted research, hit highlighting, and so much more all with NoSQL Functionality.
To engineer high-performance programs, our developers use Apache Pig since it seems to run seamlessly on Apache Hadoop, as well as MapReduce and Apache Spark.
To manage Apache Hadoop jobs as a workflow scheduling system, our developers use Apache Oozie, which is highly effective in executing accurate scheduling.
Our
Portfolio
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1500 Concord Ter.
Suite 100,
Sunrise, FL 33323
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