Apache Graduates Another Big Data Project to Top Level

For the past year, 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.

Only days ago, the foundation announced that Apache Kudu has graduated from the Apache Incubator to become a Top-Level Project (TLP). Kudu is an open source columnar storage engine built for the Apache Hadoop ecosystem designed to enable flexible, high-performance analytic pipelines. And now, Apache Twill has graduated as well. Twill is an abstraction over Apache Hadoop YARN that reduces the complexity of developing distributed Hadoop applications, allowing developers to focus more on their application logic.

"The Twill community is excited to graduate from the Apache Incubator to a Top-Level Project," said Terence Yim, Vice President of Apache Twill and Software Engineer at Cask. "We are proud of the innovation, creativity and simplicity Twill demonstrates. We are also very excited to bring a technology so versatile in Hadoop into the hands of every developer in the industry."

Apache Twill focuses on features for common distributed applications for development, deployment, and management, and is targeted to ease Hadoop cluster operation and administration.

"Enterprises use big data technologies - and specifically Hadoop - to drive more value," said Patrick Hunt, member of the Apache Software Foundation and Senior Software Engineer at Cloudera. "Apache Twill helps streamline and reduce complexity of developing distributed applications and its graduation to an Apache Top-Level Project means more people will be able to take advantage of Apache Hadoop YARN more easily." Cloudera, of course, has a long and storied history with Hadoop.

“This is an exciting and major milestone for Apache Twill,” said Keith Turner, member of the Apache Fluo (incubating) Project Management Committee, which used Twill in the development of Fluo, an Open Source project that makes it possible to update the results of a large-scale computation, index, or analytic as new data is discovered. "Early in development, we knew we needed a standard way to launch Fluo across a cluster, and we found Twill. With Twill, we quickly and easily had Fluo running across many nodes on a cluster."

 "The Apache Twill community worked extremely well within the incubator environment, developing and collaborating openly to follow The Apache Way," said Henry Saputra, ASF Member and member of the Apache Twill Project Management Committee. "There is a tremendous demand for effective APIs and virtualization for developing big data applications and Apache Twill fills that need perfectly. We’re looking forward to continuing the journey with Apache Twill as a Top-Level Project."

Here is more on 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.