Meetups & Events
September 13, 2017
In his talk, Denis will look at some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for big data analysis.
August 23, 2017
If downtime is not an option for you, and your application needs to be extremely low-latency, Kubernetes® and Apache® Ignite™ are open source frameworks that work exceedingly well together to achieve these goals.
In this webinar, Dani Traphagen will walk through the basics of a Kubernetes and Apache Ignite deployment, including:
- Setting up a Apache Ignite cluster
- Using the Kubernetes IP Finder and the Kubernetes Ignite Lookup Service
- Sharing the Ignite Cluster Configuration
- Deploying your Ignite Pods
- Adjusting the Ignite Cluster Size when you need to scale
August 16, 2017
Apache Ignite is an open source memory-centric platform that combines a distributed SQL database with a Key-Value Data Grid that is ACID-compliant and horizontally scalable. It enables high-performance transactions, real-time streaming, and fast analytics in a single, comprehensive data access and processing layer.
In this webinar, attendees will learn about the many components of Apache Ignite, including the Data Grid, Compute Grid, distributed SQL database and the Machine Learning Grid. We will also cover a few typical use cases and work through some Java code examples.
August 02, 2017
In this session, Valentin Kulichenko, Apache Ignite Committer and PMC, will give an overview of some of Apache® Ignite™ capabilities that allow the delivery as much availability as possible, while not breaking data consistency. Valentin will give specific guidelines on how to build such systems, and will do a deep dive into topics like:
- In-memory backups
- Data persistence
- Data center replication
- Full and incremental snapshots
Jul 27, 2017
Apache Ignite is one of the fastest growing Apache projects. The presentation will take the audience on a roadmap discovery of Ignite moving to a memory-centric storage model, supporting both, fast in-memory and durable on-disk data, and blending a distributed SQL database with an in-memory key-value data grid.
July 26, 2017
Join Akmal Chaudhri as he introduces the many components of the open-source Apache Ignite. You, as a Java professional, will learn how to solve some of the most demanding scalability and performance challenges. He will also cover a few typical use cases and work through some code examples.
July 19, 2017
During this session, Akmal Chaudhri will do a deep-dive on the architecture of Apache Ignite's ACID-compliant transactional subsystem, elaborating on the following:
- Data consistency: one-phase and two-phase commit implementations.
- Fault-tolerance: recovery protocol for running transactions.
- Optimistic and Pessimistic transactions.
- Deadlock-free transactions
- Deadlock detection mechanism
June 20, 2017 @6:30pm
During this session, Denis will explain how Apache Ignite handles auto-loading of SQL schema and data from MySQL, supports SQL indexes, compound indexes support, and various forms of SQL queries including distributed SQL joins. He will demostrate how to:
- Import SQL schema from MySQL and preserve the data sets stored in MySQL and Apache Ignite in sync.
- Connect to Apache Ignite from your favourite tool or application language using ODBC or JDBC driver and start talking to a clustered data using familiar statements like SELECT, UPDATE, DELETE or INSERT.
- Boost application performance 1,000x and scale to over 1 billion transactions per second with in-memory storage of hundreds of TB's of data for your SQL-based applications.
June 16, 2017 @8:00am
Apache Ignite Community decided to gather and dive into the details of Ignite Persistent Store donation to the main code base.
It’s planned to give a general overview of the store learning more about its main capabilities and features as well as go over implementation details referring to the source code.
To join use the details below.
Please join my meeting from your computer, tablet or smartphone.
https://global.gotomeeting.com/join/818661157
You can also dial in using your phone.
United States: +1 (571) 317-3112
Access Code: 818-661-157
June 07, 2017 @3:20pm
During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:
- Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
- Real-time data processing with Apache Spark and Apache Ignite.
June 07, 2017 @11:00am PT / 2:00pm ET
Apache Ignite 2.0 is a turnkey release which blends a distributed in-memory SQL database (IMDB) and an in-memory key-value data grid (IMDG) under one data management platform. It is also a necessary stepping stone ahead of Ignite 2.1 release which will be focused around the native disk persistence, allowing Ignite operate equally well in-memory and on-disk. You will learn how the off-heap memory architecture in Ignite has been re-engineered to better support SSD or Flash-based persistence. The new off-heap design uses a page-based approach with slab memory allocation, which may be optionally mapped to a persistent storage as is, without having to serialize or deserialize the data. The new architecture automatically handles memory fragmentation, significantly accelerates SQL, and almost completely removes costly garbage collection pauses. You will also learn how to create and alter SQL indexes at runtime, as well as utilize DDL to update distributed data sets using standard SQL syntax. We will also cover B+Tree data structures used to store SQL indexes off-heap.
May 18, 2017 @2:40pm
During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:
- Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
- Real-time data processing with Apache Spark and Apache Ignite.
May 18, 2017 @10:00am
In-memory data grids bring exceptional performance and scalability gains to applications built on top of them. The applications truly achieve 10x more performance improvement and become easily scalable and fault-tolerant thanks to the unique data grids architecture. However, because of this particular architecture, a majority of data grids have to sacrifice traditional SQL support requiring application developers to completely rewrite their SQL-based code to support data grid specific APIs.
May 17, 2017 @6:00pm
During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:
- Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
- Real-time data processing with Apache Spark and Apache Ignite.
May 12, 2017
There's an ad saying that Hazelcast is up to 50% faster than Apache Ignite, but that may not be true anymore. Check out this benchmark to get the true story.
May 10, 2017 @6:30pm
Akmal B. Chaudhri will be giving a quick introduction of Apache Ignite, its main capabilities and how it can add value to your pipelines. Akmal is a Technical Evangelist for GridGain, specializing in Big Data, NoSQL and NewSQL database technologies.
May 10, 2017 @5:05pm
Is memory the new disk? If so, what does this mean for the future of database systems and persistence as we know it? Will all our data(bases) still belong to us? Dani Traphagen explores the key paradigm shifts currently impacting those Fortune 500 companies that view disk as a bottleneck. Dani explains how to optimize toward the cache, leveraging it for low-latency, highly available microservices architectures with the hot-and-fresh-out-of-the-kitchen open source project Apache Ignite.
May 10, 2017 @11:00am
During this 1-hour webinar, Denis will explain and demonstrate how to build a fast data solution that can receive endless IoT-generated streams and process them in real-time using Apache Ignite's distributed in-memory computing platform. In particular, you will learn the following:
- How to stream data to an Apache Ignite cluster from embedded devices
- How to conduct real-time data processing on this stream using Apache Ignite
This major release was under the development for a long time. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. Curious why are we so boastful about this? Some of the main features of Apache Ignite 2.0 are:
- Re-engineered Off-Heap Memory Architecture
- Data Definition Language
- Machine Learning Grid Beta - Distributed Algebra
- Integration with Spring Data, Rocket MQ, Hibernate 5
- Enchanced Inite.Net and Ignite C++ APIs
See release notes for a full list of the changes.
April 25, 2017 @1:20pm PT
How to overcome the limitations of the MySQL architecture for big data analytics by leveraging the parallel distributed computing and ANSI SQL-99 capabilities of Apache Ignite. How to use Apache Ignite as an advanced high performance cache platform for hot data. The strategic benefits of using Apache Ignite instead of memcache, Redis®, Elastic®, or Apache® Spark™. At the end of the session, you will understand how incorporating Apache Ignite into your architecture can empower dramatically faster analytics and transactions when augmenting your current MySQL infrastructure.
April 19, 2017 @11:00am PT / 2:00pm ET
When systems that rely on microservices are used under high load or have to process rapidly growing volumes of data,
they usually face the same issues and difficulties as applications that are not microservices-based. Disk-backed databases become a
performance bottleneck as they can no longer keep up with growing volumes of data that have to be stored and processed in parallel.
This degrades application performance and ultimately causes instability.
This webinar discusses how in-memory computing using Apache® Ignite™ can overcome the performance limitations
common to microservices architectures built using traditional database architectures.
April 7, 2017 @15:30pm
In-memory computing frameworks and products rely on a simple horizontal scalability property - the more machines we have in a cluster the better the performance. However, a reasonable question arises. If I add a second machine to the cluster will I get 2x improvement? If there are 10 machines in a cluster should I expect overall 10x performance increase? Is it true and if, yes, if the guarantee meets all the time? Join Yakov on his talk to get answers on these questions and learn more about scalability and concurrency concepts implemented in Apache Ignite In-Memory Data Fabric.
April 4, 2017 @15:15pm
In-memory computing frameworks and products rely on a simple horizontal scalability property - the more machines we have in a cluster the better the performance. However, a reasonable question arises. If I add a second machine to the cluster will I get 2x improvement? If there are 10 machines in a cluster should I expect overall 10x performance increase? Is it true and if, yes, if the guarantee meets all the time? Join Yakov on his talk to get answers on these questions and learn more about scalability and concurrency concepts implemented in Apache Ignite In-Memory Data Fabric.
March 30, 2017 @14:00pm EDT
Learn how to boost performance 1,000x and scale to over 1 billion transactions per second with in-memory storage of hundreds of TBs of data for your SQL-based applications. Apache Ignite is a unique NewSQL platform that is built on top of a distributed key-value storage and provides full-fledged SQL support. Denis will show how Apache Ignite handles auto-loading of SQL schema and data, SQL indexes, compound indexes support, and various forms of SQL queries including distributed SQL joins. It will be demonstrated how to connect to Apache Ignite from your favorite tool or application language using ODBC or JDBC driver and start talking to a clustered data using familiar statements like SELECT, UPDATE, DELETE or INSERT.
March 28, 2017 @1:00pm PT
In this presentation, Denis will introduce Apache Ignite SQL Grid component that combines the best of two worlds - performance and scalability of data grids and traditional ANSI-99 SQL support of relational databases. Moreover, Denis will take an existing application that works with a relational database and will show how to run it on top of Apache Ignite with minimum efforts.
March 24, 2017 @15:00pm
Join and learn about Apache Ignite which is a high-performance, integrated and distributed in-memory platform 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.
March 15, 2017 @11:00am PT / 2:00pm ET
During this webinar, Apache Ignite PMC chair Denis Magda will introduce the SQL Grid component of Apache® Ignite™. He will discuss:
- ANSI-99 SQL queries including distributed joins
- Creating and leveraging SQL indices
- Data modification with ANSI-99 DML (INSERT, UPDATE, DELETE, etc.)
- Using Apache Ignite's JDBC and ODBC drivers
February 23, 2017
IHS Markit will present first on how they have been using Apache Ignite on several major projects. The 2nd part of the meetup will be led by Mandhir Gidda, GridGain's new EMEA Solution Architect who's been working with in-memory technologies for nearly 10 years.
February 15, 2017 @11:00am PT / 2:00pm ET
During this webinar, Apache Ignite PMC chair and GridGain Systems Product Manager Denis Magda will demonstrate how Apache® Ignite™ Web Console enables automatic integration of Apache Ignite and your RDBMS. He will show you how to:
- Import a RBMS schema and map it to the Apache Ignite caches
- Setup indexes
- Create a Java POJO
- Download a ready-to-run Apache Ignite based project that will be fully integrated with the RDBMS
January 25, 2017 @11:00am PT / 2:00pm ET
GridGain Systems Solution Architects Christos Erotocritou and Rachel Pedreschi have helped numerous customers get started with Apache® Ignite™ and GridGain. During this 1-hour webinar, they will share answers to the most common questions asked prior to deployment. They will also provide guidance that will save you time and make deploying GridGain or Apache Ignite a more enjoyable experience.
This new release includes SQL DML operations support (INSERT, UPDATE, DELETE, MERGE) in Java, MapR distribution support in Hadoop, Entity Framework 2nd level cache and ASP.NET session state cache in .NET, DML and distributed joins in ODBC, stability and performance improvements, and more.
November 16, 2016
Join Dmitriy Setrakyan, Apache Ignite Project Management Committee Chairman and co-founder and Chief Product Officer at GridGain, to learn more about the need to share state across different Spark jobs and applications and several technologies that make it possible, including Tachyon and Apache Ignite.
November 16, 2016
Learn the importance of In Memory File Systems, Shared In-Memory RDDs with Apache Ignite, as well as the need to index data in-memory for fast SQL execution.
November 15, 2016
The presentation will take the audience on a roadmap discovery of Ignite moving to a converged storage model, supporting both, analytical and transactional data sets.
This new release includes support for distributed SQL JOIN, decimal support in ODBC, custom affinity functions and ASP.NET Output Cache Provider in .NET, stability and performance improvements, and more.
Join us for a technical session to look at Apache Ignite and hear from BlackRock on how they believe it will solve their application performance & scalability challenges.
Please RSVP on Meetup.com.
Apache Ignite PMC member, Nikita Ivanov will be presenting a deep dive on Apache Ignite at our NYC meetup, Tuesday, June 28 at Work Market, 240 W 37th St, 9th Floor, New York, NY.
Please RSVP on Meetup.com. Space is limited and is filling up fast!
This new release includes support for deadlock detection in Ignite caches, ODBC driver, CacheStore implementation backed by Cassandra DB, AtomicSequence and AtomicReference data structures for .NET, transactions API for C++ client, stability and fault-tolerance improvements, and more.
Add-ons has been added to the website for projects built on top of Ignite. These projects intend to make user experience with Ignite easier. Currently, there are two such projects available - Apache Ignite Extensions and GridGain Web Console.
This final version of 1.5.0 includes support for .NET and C++, Streamer for MQTT, Twitter, Apache Flume, and Apache Camel, OSGi support, "deadlock-free" transactions, compact binary protocol, performance improvements for SQL queries, transactions, and more.
This early access version includes support for .NET and C++, Streamer for MQTT, Twitter, and Apache Flume, compact binary protocol, performance improvements for SQL queries, transactions, and more.
This is the first Apache Ignite release since the project graduated from incubation in August, 2015. This new release includes SSL support to communication and discovery, support for log4j2, significantly faster JDBC driver implementation, fixes for SQL queries group index logic, auto-retries for cache operations in recoverable cases and more.
The Apache Software Foundation (ASF), the all-volunteer developers, stewards, and incubators of more than 350 Open Source projects and initiatives, announced today that Apache™ Ignite™ 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.
This new release includes integration with Apache YARN for data center and resource management, fixes for JTA transactions, Hibernate L2 Cache improvements, and more.
This new release includes shared RDD for Apache Spark (based on Ignite Data Grid), integration with Apache Mesos for data center management, client-mode for light-weight cluster discovery, memory-size eviction policy, and more.
This new release includes Google Compute Engine and generic cloud TCP discovery IP finder, "Collocated" mode for SQL queries, support for (*) star notation in cache names, fix for SQL union support, and more.
This new release includes dynamic caching functionality to start and stop caches during runtime, simplified Query API, automatic aggregation, grouping and sorting support for SQL Queries, Streaming examples, and more.
This is the first release of Apache Ignite project. The source code in large part is based on the GridGain In-Memory Data Fabric, open source edition, v. 6.6.2, which was donated to Apache Software Foundation. The main feature set of Ignite In-Memory Data Fabric includes:
- Advanced Clustering
- Compute Grid
- Data Grid
- Service Grid
- IGFS - Ignite File System
- Distributed Data Structures
- Distributed Messaging
- Distributed Events
- Streaming & CEP
InfoQ caught up with Nikita Ivanov, CTO and founder of GridGain, about the In-Memory Computing framework becoming an Apache project, motivation behind this decision, and upcoming features and enhancements of GridGain.
GridGain recently announced that the GridGain In-Memory Data Fabric has been accepted into the Apache Incubator program under the name "Apache Ignite." Earlier in 2014, GridGain was transformed to an open source model through Apache 2.0 license. Now, the product will be available under the Apache Foundation project portfolio.