BIG DATA SOLUTION WITHIN YOUR REACH
Yava – Data Management Platform is a 100% open source compilation of Big Data platform that use of the power of Apache Hadoop ecosystem and designed to help accelerate the adoption of Hadoop implementation and its ecosystem in Indonesia.
YAVA Data Management Platform, or commonly referred to YAVA is an open source compilation platform that provides a big data management environment with management and monitoring of Hadoop cluster. A combination between the power of Apache Hadoop ecosystem and ease of use, YAVA designed to help accelerate the adoption of Hadoop implementation.
Integrated Data Platform
YAVA provides a wide range of data access dan processing capabilities: batch, streaming, interactive, SQL and real time in a single cluster. It will enables you to analyze data for various use cases to get deep data insights that can transform your business
Reliability and Flexibility
Hadoop and its ecosystem has been proven for more than a decade in fast, effective and efficient large-scale data processing. With Yava, you can take all the power of hadoop and implement it as needed
YAVA is built on top of the Apache projects, giving you the advantage of the best technology with wide range of supporters and adopters. By choosing and orchestrating the latest and most stable versions of various components, you will avoid the risk of vendor lock-in solution.
YAVA is interoperable with a broad ecosystem, moving data from and to YAVA to other system can be done easily. It allows you to reduce cost and effort, and preserve investment in your IT architecture.
YAVA delivered with security, centralized cluster management and integrated monitoring that enable multiple workloads simultaneously. You can answer all enterprise demand.
One of the challenges in using open source technology is support. YAVA is supported in terms of platform lifecycle, implementation, operations and knowledge. You can get community or commercial support
Data Store and Resource Manager
Reliability and linear scalability of HDFS provides storage for data with a variety of formats. Providing a broad selection of solutions based on the needs and available resources by supporting both commodity servers and high-level servers. YARN cluster management system enables various processes running on top of HDFS.
With the support from YARN cluster management, Yava provides a wide range of data access and processing capabilities: batch, streaming, interactive and real time in a single cluster.
MapReduce for batch processing, Phoenix, Hive and Tez for SQL based processing, scripting with Pig, HBase for NoSQL, searching with Solr, streaming with Storm, Spark for in memory process, and Mahout for data mining and machine learning. Yarn resource manager allows a cluster to fulfill different processing needs, avoiding costly and inconvenient redundancy of data.
Apache Sqoop allows effective data transfer between Hadoop and structured data sources such as Teradata, Netezza, Oracle, MySQL, Postgres and HSQLDB.
Apache Flume is used for streaming large amounts of data into HDFS, for example, logs from the production machine or network. Flume provides simple and flexible architecture, with reliable failover and recovery mechanisms.
Apache Ambari is a framework for provisioning, managing and monitoring Apache Hadoop cluster. Ambari provides a simple and elegant user interface. It can be integrated with existing operational tools, such as Microsoft System Center and Teradata Viewpoint.
Apache Zookeeper™ provides a distributed configuration, synchronization, and naming registry for distributed systems. Zookeeper is used to store and manage critical changes in configurations.
Apache Oozie provides the tools for workflow scheduling to manage jobs in Enterprise Hadoop.
HGrid247 is a comprehensive ETL process designer. Hgrid247 ease of use and intuitive drag-and-drop interface simplify and reduce time and complexity of data integration. By eliminating Java or other programming for MapReduce, Spark, Storm and Tez jobs and scripts, HGrid247 empowers developers and designers to develop big data jobs using visual tools. This will speed up the work and increase team productivity, because ETL/ELT developers and designers can focus on the design of the process.
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HADOOP, the Hadoop Elephant Logo, Apache, Flume, Ambari, Yarn, Bigtop, Phoenix, Hive, Tez, Oozie, HBase, Mahout, Pig, Solr, Storm, Spark, Sqoop, Impala, and ZooKeeper are registered trademarks or trademarks of the Apache Software Foundation.