Apache Geode Graduates to Top Level Project in Apache; Up Next: Microservices

Cross posted from The Pivotal Blog.

Just eighteen months ago Pivotal granted over 1 million lines of code from the Pivotal GemFire code base to The Apache Software Foundation (ASF) to help create the Apache Geode project. We made this decision because we saw many of our enterprise customers gravitating towards open source software-based solutions as part of larger IT modernization efforts. These customers understand products based on open source projects often evolve faster than their closed-source counterparts, provide more roadmap and release transparency, and reduce the risk of vendor lock-in. We couldn’t agree more.

Apache Geode began as a podling in the Apache Incubator project. Since then, an active community of contributors has grown around the project, helping improve and add capabilities to the in-memory data grid. Given the role in-memory data grids and event-driven architectures play in building cloud-native applications, the interest in Apache Geode is no surprise.

It’s been an active and fruitful year for Apache Geode. The first Apache Geode Summit was held in March 2016 and drew close to 100 community members from enterprises including Bloomberg, Southwest Airlines, Murex and TEKsystems, among others. In October 2016, Apache Geode 1.0 was released, a major milestone for any open source project. And now, the Apache Geode community has achieved an important milestone! Pivotal is thrilled that just this week the ASF graduated Apache Geode to 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.” We extend a hearty congratulations to the Apache Geode community, without whom TLP graduation couldn’t have been achieved. This truly was a community effort, representing the best of open source and the “Apache Way”!

Of course, Apache Geode’s graduation to TLP is just one step in a longer journey to help enterprises across industries support mission critical applications with a modern, open-source based, in-memory data grid. This includes supporting an event-driven and microservices-based approach to application architecture. Microservice are autonomous across a network boundary, and inter-microservice communication is best handled through an event-driven approach – a sweet spot for Geode.

Geode and Microservices

Over the last few years, a microservices-based approach has emerged as the ideal way to build web-scale, applications, and more and more enterprises are looking to adopt this pattern for their custom software. The benefits of this approach are compelling, given the availability, scale, and speed that companies like Netflix have achieved.

Here at Pivotal, we’ve been at the forefront of the rise of microservices, with Spring Boot as the de facto Java framework, Spring Cloud Services based on Netflix OSS, and Pivotal Cloud Foundry for continuous integration and delivery. So, how does Geode fit in with this movement?

It turns out Geode is a perfect complement to a microservices architecture thanks to joint development work from the Spring and GemFire teams, the results of which have been extended into Spring Data Geode. In terms of microservices, there are implications for how data is managed when breaking applications down into specific, autonomous services that can be developed and scaled independent of one another, including how data is communicated and shared between different microservices.

From an architectural perspective, an event-based architecture is ideally suited for interactions between these loosely coupled microservices. Fortunately, Geode was designed for event-based architectures and naturally supports a microservices application development approach. The Geode Continuous Query feature, for example, can be used within each microservice for specifying state changes the microservices wants to subscribe to. The events that are of interest to a microservice can be easily specified using OQL. This convergence of features in Geode that fulfill the requirements of microservices is no accident – it is part of Geode’s design. The blazing fast performance of in-memory computing, coupled with an event-based architecture, make Geode an attractive choice for supporting microservices-based applications.

Geode also benefits from over ten years of development (as GemFire), maturing within numerous enterprises, and now advancing through community-based, meritocratic development. The seemingly daunting data challenges of microservices can be met without compromising the benefits of microservices.

Again, a big congratulations to the Apache Geode community for achieving this historic milestone! We at Pivotal look forward to continuing to work closely with the community and Pivotal customers to move the project forward. The sky’s the limit for Apache Geode! Interested in learning more about Apache Geode? Check out this five minute Geode tutorial, ask questions on the Geode mailing lists or on StackOverflow, or download Geode here.

Two Reasons Why In-Memory Data Grids Are A Must-Have For Apps at Scale

Cross posted from The Pivotal POV Blog…

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Pivotal is proud to announce that Pivotal GemFire was cited as a leader in newly published the Forrester Wave™: In-Memory Data Grids, Q3 2015 report from Forrester Research. The report evaluated the respective in-memory solutions against 32 criteria in three high-level buckets of current offering, strategy, and market presence. GemFire was cited among the second-highest in the strategy category. Forrester provides the following comments about GemFire: [Read more…]

Apache Geode Update

Cross posted from The Pivotal POV Blog…

It’s been a fsfeatured-geodeew months since Project Geode, the open source core of Pivotal Gemfire, was announced. Since then, the Apache Software Foundation accepted Pivotal’s proposal to incubate Geode as a collaborative development project, and we’ve successfully moved all the project interaction onto the Apache infrastructure. You now have the opportunity to support the powerful Geode technology, which powers commercial high scale banking applications, Internet of Things in-memory analytics, and scale-out digital customer experience infrastructure, such as servicing digital ticket purchases for the largest human migration in the world during Chinese New Year.

Here’s where you can find the Apache Geode project, get hold of the software, and interact with the community:

[Read more…]

Become A Founding Contributor of “Project” Geode

Cross posted from The Pivotal POV Blog…

featured-project-geode-250x250Today, Pivotal announced the creation of “Geode”, the new in-memory distributed database that will form the open source core of Pivotal GemFire.

It is my pleasure to announce the really fun part of this: the beginning of “Project Geode” – the community of users of and contributors to the Geode technology.

As part of this announcement, we stated that Pivotal has submitted a proposal to The Apache Software Foundation (ASF) to establish and incubate Project Geode through collaborative development.

[Read more…]

Pivotal Releases GemFire 8.1 With Updates and New Features

Cross posted from The Pivotal POV Blog…

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Pivotal GemFire 8 was the first major release of the in-memory distributed database since it joined Pivotal’s portfolio of products. Today, we’re announcing the release of Pivotal GemFire 8.1. Part of the Pivotal Big Data Suite, Pivotal GemFire enables developers to deploy their big data NoSQL apps upon a massive scale. In addition to incremental product improvements, 8.1 enhances GemFire’s availability and resilience within a distributed system, and improves upon its management and monitoring features.

Allowing High Availability, Resilience, and Global Scale

[Read more…]

GemFire XD 1.4 Now Available for Download

Cross posted from The Pivotal POV Blog…

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The latest release of GemFire XD, version 1.4 is now available for download. its biggest improvements include single hop inserts for 50% faster performance, and support for JSON document objects in SQL tables. This makes GemFire XD even better for write-intensive use cases, such as high-speed ingest. Also, now we can support use cases that need more schema flexibility to the otherwise well-defined relational structure of GemFire XD.

[Read more…]

10 Amazing Things to Do With a Hadoop-Based Data Lake

Cross posted from The Pivotal POV Blog.

The following is a summary of a talk I gave at Strata NY that is proving popular among a lot of people who are still trying to understand use cases for Apache Hadoop® and big data.  In this talk, I introduce the concept of a Big Data Lake, which utilizes Apache Hadoop® as storage, and powerful open source and Pivotal technologies. Here are 10 amazing things companies can do with such a big data lake, ordered according to increasing impact on the business.

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Announcing the New Version of GemFire XD and SQLFire: Pivotal GemFire XD 1.3

Cross posted from my blog at Pivotal POV…

 

 

The newest versions of SQLFire and GemFire XD are one and the same: Pivotal GemFire XD version 1.3. What were previously two separate products are now merged, so current licensees of either product are entitled to upgrade to the new version.

[Read more…]

What’s New in Pivotal GemFire 8

Reposted from Pivotal POV….

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On September 23, 2014 Pivotal announced the release of Pivotal GemFire 8, part of Pivotal Big Data Suite. This is the first major release of GemFire since it became part of the Pivotal portfolio.

Born from the experience of working with over 3000 of the largest in-memory data grid projects out there, including China Railways, GIRE, and Southwest Airlines, and  we’ve invested more into the needs of the most demanding enterprises: more scale, more resilience, and more developer APIs.

This release is a significant enhancement for developers looking to take their big data NoSQL apps to massive scale. For the complete technical details, you can check out the new datasheet, and official product documentation.

Here’s what’s new, sorted by the 5 areas that GemFire does best in the industry:

Providing Scale Out Performance

This is why most of Pivotal’s customers begin looking at GemFire in the first place—because they can’t make traditional RDBMS’s scale with the number of concurrent transactions and data they need to manage.

Pivotal GemFire manages data in-memory distributed across multiple systems on commodity hardware—100’s of nodes if you like—in a shared-nothing architecture.  So there’s plenty of compute and memory to host all your data to get real-time response.

WHAT’S NEW

We’ve added in-memory compression, effectively giving each node the capacity to hold up to 50% more data. Compression is achieved through Snappy, a speed-optimized algorithm, although the compression codec is replaceable to whatever algorithm you want to use.

Maintaining Consistent Database Operations Across Globally Distributed Nodes

[Read more…]