Apache OODT Big Data Project, Used By NASA and Others, Moves Forward

In recent coverage, we've taken note of the many projects that the Apache Software Foundation has been elevating to Top-Level Status. The organization incubates more than 350 open source projects and initiatives, and  has squarely turned its focus to Big Data and developer-focused tools in recent months. As Apache moves Big Data projects to Top-Level Status, they gain valuable community support and more. Just this week, we reported on Bahir moving to Top-Level Status. Bahir bolsters Big Data processing by serving as a home for existing connectors that initiated under Apache Spark, and provides additional extensions/plugins for other related distributed system, storage, and query execution systems.

Now, Apache has announced the availability of Apache OODT v1.0, a Big Data middleware metadata framework.

According to Apache:

"OODT is a grid middleware framework for science data processing, information integration, and retrieval. As 'middleware for metadata' (and vice versa), OODT is used for computer processing workflow, hardware and file management, information integration, and linking databases. The OODT architecture allows distributed computing and data resources to be searchable and utilized by any end user."

"Apache OODT 1.0 is a great milestone in this project," said Tom Barber, Vice President of Apache OODT. "Effectively managing data pools has historically been problematic for some users, and OODT addresses a number of the issues faced. v1.0 allows us to prepare for some big changes within the platform with new UI designs for user-facing apps and data flow processing under the hood. It’s an exciting time in the data management sector and we believe Apache OODT can be at the forefront of it."

 OODT has been hardened through use at notable institutions. Originally created at NASA Jet Propulsion Laboratory in 1998 as a way to build a national framework for data sharing, OODT has been instrumental to the National Cancer Institute’s Early Detection Research Network for managing distributed scientific data sets across 20+ institutions nationwide for more than a decade.

Apache OODT is in use in many scientific data system projects in Earth science, planetary science, and astronomy at NASA, such as the Lunar Mapping and Modeling Project (LMMP), NPOESS Preparatory Project (NPP) Sounder PEATE Testbed, the Orbiting Carbon Observatory-2 (OCO-2) project, and the Soil Moisture Active Passive mission testbed. In addition, OODT is used for large-scale data management and data preparation tasks in the DARPA MEMEX and XDATA efforts, and for supporting research and data analysis within the pediatric intensive care domain in collaboration with Children's Hospital Los Angeles (CHLA) and its Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit (VPICU), among many other applications.

Here is more on many other Apache Big Data projects that are moving forward:

Allura. According to the Allura project page, new features include an Admin Nav Bar, which is a an improvement on how users customize the tools of a project. There is also a new interface. Apache encourages users to read an admin toolbar post to see how easy it is to access tool configurations and add new tools with Allura.

Brooklyn. The foundation announced that Apache Brooklyn is now a Top-Level Project (TLP), "signifying that the project's community and products have been well-governed under the ASF's meritocratic process and principles."  Brooklyn is an application blueprint and management platform used for integrating services across multiple data centers as well as and a wide range of software in the cloud.

According to the Brooklyn announcement:

"With modern applications being composed of many components, and increasing interest in micro-services architecture, the deployment and ongoing evolution of deployed apps is an increasingly difficult problem. Apache Brooklyn’s blueprints provide a clear, concise way to model an application, its components and their configuration, and the relationships between components, before deploying to public Cloud or private infrastructure. Policy-based management, built on the foundation of autonomic computing theory, continually evaluates the running application and makes modifications to it to keep it healthy and optimize for metrics such as cost and responsiveness."

Brooklyn is in use at some notable organizations. Cloud service providers Canopy and Virtustream have created product offerings built on Brooklyn. IBM has also made extensive use of Apache Brooklyn in order to migrate large workloads from AWS to IBM Softlayer.

Kylin. Meanwhile, the foundation has also just announced that Apache Kylin, an open source big data project born at eBay, has graduated to Top-Level status. Kylin is an open source Distributed Analytics Engine designed to provide an SQL interface and multi-dimensional analysis (OLAP) on Apache Hadoop, supporting extremely large datasets. It is widely used at eBay and at a few other organizations.

"Apache Kylin's incubation journey has demonstrated the value of Open Source governance at ASF and the power of building an open-source community and ecosystem around the project," said Luke Han, Vice President of Apache Kylin. "Our community is engaging the world's biggest local developer community in alignment with the Apache Way."

As an OLAP-on-Hadoop solution, Apache Kylin aims to fill the gap between Big Data exploration and human use, "enabling interactive analysis on massive datasets with sub-second latency for analysts, end users, developers, and data enthusiasts," according to developers. "Apache Kylin brings back business intelligence (BI) to Apache Hadoop to unleash the value of Big Data," they added.

Lens. Apache recently announced that Apache Lens, an open source Big Data and analytics tool, has graduated from the Apache Incubator to become a Top-Level Project (TLP).

According to the announcement:

"Apache Lens is a Unified Analytics platform. It provides an optimal execution environment for analytical queries in the unified view. Apache Lens aims to cut the Data Analytics silos by providing a single view of data across multiple tiered data stores."

"By providing an online analytical processing (OLAP) model on top of data, Lens seamlessly integrates Apache Hadoop with traditional data warehouses to appear as one. It also provides query history and statistics for queries running in the system along with query life cycle management."

 "Incubating Apache Lens has been an amazing experience at the ASF," said Amareshwari Sriramadasu, Vice President of Apache Lens. "Apache Lens solves a very critical problem in Big Data analytics space with respect to end users. It enables business users, analysts, data scientists, developers and other users to do complex analysis with ease, without knowing the underlying data layout."

Ignite. The ASF has announced that Apache Ignite is to become a top-level project. It's an open source effort to build an in-memory data fabric that was driven by GridGain Systems and WANdisco.

Apache Ignite is a high-performance, integrated and distributed In-Memory Data Fabric for computing and transacting on large-scale data sets in real-time, "orders of magnitude faster than possible with traditional disk-based or flash technologies," according to Apache. It is designed to easily power both existing and new applications in a distributed, massively parallel architecture on affordable, industry-standard hardware.

Tajo. Apache Tajo v0.11.0, an advanced open source data warehousing system in Apache Hadoop, is another new Top-Level project. Apache claims that Tajo provides the ability to rapidly extract more intelligence fro  Hadoop deployments, third party databases, and commercial business  intelligence tools.

And of course, Spark and other previously announced Big Data tools overseen by Apache are flourishing. Look for many more data- and developer-focused tools to move forward at Apache in the months to come.