Kudu and Apache Big Data Tools are Drawing Much Attention
As I noted at the end of last year, the Apache Software Foundation, which incubates more than 350 open source projects and initiatives, squarely turned its focus to Big Data tools in 2015. You can expect more in 2016, as a number of incubated projects graduate to Top-Level Status at Apache, which helps them get both advanced stewardship and certainly far more contributions.
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, and you'll find more details in this post. Kudu is an open source storage engine for structured data
which supports low-latency random access together with efficient analytical access patterns.
Kudu is designed within the context of the Hadoop ecosystem and supports many access on-ramps, inclduing 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."
Kudu is not the only Big Data tool to cross the transom at the Apache Software Foundation. Here are some of the other notable projects the foundation 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.