Apache Apex Joins a Slew of Free Tools for Next-Gen Big Data
As I've noted in some recent posts, the Apache Software Foundation, which incubates more than 350 open source projects and initiatives, squarely turned its focus to Big Data tools in 2015. There are also clear signs that it is continuing to do so as 2016 launches. One of the more interesting tools on this front is Kudu, which Cloudera has offered to the Apache Software Foundation for open source stewardship. Cloudera has a whole whitepaper on Kudu here, but its far from the only big data tool that is attracting TLC from Apache.
Apache Apex has rapidly moved from code to acceptance within the Apache Software Foundation. It became enabled when YARN arrived, and here is more about it and other notable Apache Big Data tools that you can use for free.
"Apache Apex is the first ever YARN native engine. This native architecture allows Apache Apex to fulfil the decade-old promise of productizing Hadoop. Because big data is tough to envisage in its entirety, the platform had to be created to become the basis for driving big data processing needs, in a batch paradigm, streaming paradigm, or both. Apache Apex is the industry’s only open-source enterprise-grade engine capable of handling batch data as well as steaming data needs. Apache Apex is groomed to drive the highest value for businesses operating in highly data-intensive environments."
There is actually a whole ecosystem of tools for nex-generation data analytics coming from Apache. Kudu, another open source project on this front, is designed within the context of the Hadoop ecosystem and supports many access on-ramps, including MapReduce and Impala.
According to Cloudera's whitepaper:
"Kudu is a new storage system designed and implemented
from the ground up to fill the gap between high-throughput
sequential-access storage systems such as HDFS and low-
latency random-access systems such as HBase or Cassandra.
While these existing systems continue to hold advantages in
some situations, Kudu offers a "happy medium" alternative
that can dramatically simplify the architecture of many com-
mon workloads. In particular, Kudu offers a simple API for
row-level inserts, updates, and deletes, while providing table
scans at throughputs similar to Parquet, a commonly-used
columnar format for static data."
Here are some of the other notable projects that APACHE is overseeing:
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 of these projects to advance data analytics in 2016.