Apache Elevates Another Big Data Project to Top-Level Status
Just last week, in conjunction with covering the Allura project, I wrote about 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.
Today, the foundation announced that Apache Apex has graduated from the Apache Incubator to become 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. Apex is a large scale, high throughput, low latency, fault tolerant, unified Big Data stream and batch processing platform for the Apache Hadoop ecosystem. Here is more on the project, and Apache's other Big Data projects.
"It is very exciting to see Apex after nearly 4 years since inception becoming an ASF top-level project," said Thomas Weise, Vice President of Apache Apex. "It opens the strong capabilities and potential of the platform to a wider audience and we’re looking forward to a growing community to continue driving innovation in the stream processing space."
InfoWorld has called out Apex for its "blazing speed and simplified programmability," and it works in conjunction with Apache Hadoop YARN, a resource management platform for working with Hadoop clusters.
Apex was originally created at DataTorrent Inc. in 2012 (coinciding with the first alpha release of YARN), and entered the Apache Incubator in August 2015.
According to Apache:
"Apache Apex meets the demands of today's Big Data applications with real-time reporting, monitoring, and learning with millisecond data point precision. Its pipeline processing architecture can be used for real-time and batch processing in a unified architecture. Apex is highly performant, linearly scalable, fault tolerant, stateful, secure, distributed, easily operable with low latency, no data loss, and exactly-once semantics."
"Apex streamlines development and productization of Hadoop applications and lowers the barrier-to-entry by enabling developers to write or re-use generic Java code, minimizing the specialized expertise needed to write Big Data applications. This allows organizations to maximize developer productivity, accelerate development of business logic, and reduce time to market."
"Apache Apex is an example of the latest generation of advanced stream processing software that adds significant technology and capabilities over previous options," said Ted Dunning, Vice President of the Apache Incubator, Apache Apex Incubator Mentor, and Chief Application Architect at MapR Technologies. "That this project came to Apache and is now a fully fledged project is very exciting."
Here are some other very notable Apache tools that have been advanced and/or enhanced recently:
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.