Developers Use In-Memory Computing to Improve Application Performance
Developers must find ways to accelerate new and existing applications, achieve massive database scalability, enable real-time data access across datastores, and use technologies like machine and deep learning to power real-time decision making. Developers help their companies meet competitive demands to accelerate digital transformations, build out their applications quickly, and get it right the first time.
GridGain In-Memory Computing Solutions
GridGain offers developers the in-memory computing platform software, support, and professional services you need to better achieve your real-time digital transformation technical challenges. We also offer the free online GridGain Control Center for managing, monitoring and developing on GridGain or Ignite. The GridGain in-memory computing platform easily integrates with your new or existing applications and provides real-time performance and massive scalability.
Built on the open source Apache Ignite project, GridGain is a cost-effective solution for accelerating and massively scaling out new or existing applications with users that span a wide variety of use cases and industries.
Developers Need the GridGain In-Memory Platform
For existing applications, GridGain is typically used as an in-memory data grid between the application and data layer, with no rip-and-replace of the underlying database. For new applications, GridGain is used as an in-memory data grid or an in-memory database. A Unified API, with ANSI-99 SQL and key-value APIs among many others, and ACID transaction support provides easy integration with your new or existing code, enabling you to create modern, flexible applications built on an in-memory computing platform which will grow with your business needs. Thin and thick clients are available which support a wide variety of protocols including SQL, Java, C++, .NET, PHP, Scala, Groovy and Node.js.
How GridGain In-Memory Computing Solutions Help Developers Accelerate Applications
The white papers, webinars, application notes, product comparisons, and videos below discuss provide developers with various technical in-memory computing development examples.
Resources
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This hands-on training is for those wondering how to monitor and manage Apache Ignite clusters in production: what the most important metrics are, how to set up alerting or troubleshoot performance when the cluster is under the production load, and develop queries. The list of questions and challenges related to Ignite production monitoring goes on and on. And you’ll get many of those questions covered.
During this webinar, we review various approaches to storing and using authentication data in distributed applications. Moving from the simplest to the most complex models, we consider the pros and cons of each approach. We give special attention to one of the most popular approaches to distributed sessions—single sign-on.
As an example, we consider a secured GridGain cluster and its monitoring tool—Control Center. We see how to integrate GridGain and Control Center with various OpenID Connect providers, and learn about the advantages that such a setup offers.
Join this demo, led by Andrey Alexandrov. Andrey guides you through the internal workings of GridGain Nebula, a managed services offering for Apache Ignite and GridGain. Andrey provides a brief overview of the solution's technology stack and architecture. Then, Andrey moves to live examples of how to use GridGain Nebula to accelerate platform deployment and configuration in public clouds. You learn how to do all of the following:
The GridGain Operator for Kubernetes enables you to deploy and manage Apache Ignite and GridGain clusters efficiently. The automation that Kubernetes and the Operator provide simplifies provisioning and minimizes the operational and management burden.
During this webinar, you learn the difference between in-memory clusters and persistent clusters, move step by step through the configuration, and use The GridGain Operator for Kubernetes to deploy Apache Ignite in AWS. You will see how to do the following:
Typically, operations exceed fifty percent of the cost of an IT system’s life cycle. By developing applications that can be easily managed, developers can significantly reduce the cost of ownership. Manageability is especially important for distributed applications because they are especially complex and often mission-critical.
In this webinar, Alexey discusses the following topics:
Kafka with Debezium and GridGain connectors enables change data capture (CDC) based synchronization between third-party databases and GridGain clusters. Synchronization that is based CDC does not require coding; all it requires is to prepare configuration files for each of the points. Developers and architects who can’t yet move from a legacy system can deploy this solution to boost the performance of their applications or to enable their applications to access data from multiple data silos and store it in one place
Apache Ignite can scale horizontally to accommodate the data that your applications and services generate. However, in practice, most of us cannot scale out a cluster instantly.
In this webinar, Denis Magda will introduce several architectural techniques that can help you keep your cluster operational and your applications running even if memory becomes a scarce resource. During the webinar demo you will learn how to use those techniques in practice. Topics covered include:
Serverless computing allows you to design and build scalable cloud-native applications without thinking about infrastructure provisioning and orchestration. With Apache Ignite, you can bootstrap an in-memory cluster in the cloud and access data 100-1000x faster than with disk-based databases.
In this webinar, Denis Magda will discuss architectural patterns and design considerations for deploying Apache Ignite in a serverless computing environment. In particular, you will learn the following:
If your company is one of the tens of thousands of organizations that use Apache® IgniteTM or GridGain® Community Edition in a production environment, GridGain Basic Support can provide you with peace of mind that you have a trusted partner to help keep your environment running flawlessly. The service includes....
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Redis Enterprise (and their respective open source projects where relevant) compare in 25 categories.
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Hazelcast (and their respective open source projects where relevant) compare in 25 different categories.
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Oracle Coherence (and their respective open source projects where relevant) compare in 25 different categories.
Kafka with Debezium and GridGain connectors enables change data capture (CDC) based synchronization between third-party databases and GridGain clusters. Synchronization that is based CDC does not require coding; all it requires is to prepare configuration files for each of the points. Developers and architects who can’t yet move from a legacy system can deploy this solution to boost the performance of their applications or to enable their applications to access data from multiple data silos and store it in one place
The GridGain Operator for Kubernetes enables you to deploy and manage Apache Ignite and GridGain clusters efficiently. The automation that Kubernetes and the Operator provide simplifies provisioning and minimizes the operational and management burden.
During this webinar, you learn the difference between in-memory clusters and persistent clusters, move step by step through the configuration, and use The GridGain Operator for Kubernetes to deploy Apache Ignite in AWS. You will see how to do the following:
During this webinar, we review various approaches to storing and using authentication data in distributed applications. Moving from the simplest to the most complex models, we consider the pros and cons of each approach. We give special attention to one of the most popular approaches to distributed sessions—single sign-on.
As an example, we consider a secured GridGain cluster and its monitoring tool—Control Center. We see how to integrate GridGain and Control Center with various OpenID Connect providers, and learn about the advantages that such a setup offers.
Apache Ignite can scale horizontally to accommodate the data that your applications and services generate. However, in practice, most of us cannot scale out a cluster instantly.
In this webinar, Denis Magda will introduce several architectural techniques that can help you keep your cluster operational and your applications running even if memory becomes a scarce resource. During the webinar demo you will learn how to use those techniques in practice. Topics covered include:
Serverless computing allows you to design and build scalable cloud-native applications without thinking about infrastructure provisioning and orchestration. With Apache Ignite, you can bootstrap an in-memory cluster in the cloud and access data 100-1000x faster than with disk-based databases.
In this webinar, Denis Magda will discuss architectural patterns and design considerations for deploying Apache Ignite in a serverless computing environment. In particular, you will learn the following:
Networking is a core pillar of any distributed system and is responsible for cluster-node discovery procedures, peer-to-peer communication between nodes, and failure handling. Network architecture can greatly influence operational performance and efficiency.
This webinar will introduce you to the role of the networking layer in distributed systems with Apache Ignite as an example. You will gain practical insights and learn how to maximize the performance and reliability of your applications running on distributed systems. In particular, you will learn:
Apache Ignite and GridGain can be used as a simple cache, an in-memory data grid (IMDG), and as an in-memory database (IMDB). These data management patterns can be combined with Ignite integration facilities to function as a Digital Integration Hub (DIH) for real-time data access across data sources and applications. Common uses for the DIH architecture include:
Debugging distributed-system applications can be more complex than debugging traditional monolithic applications. As API calls jump across nodes in the cluster, it can be tricky to follow the execution just by analyzing application logs. Tracing adds a useful tool to the root-cause-analysis toolbox. Tracing makes it easier to follow the execution path, analyze timings, and align API calls with logs and stack traces. Apache Ignite 2.9 introduces new tracing instrumentation that is based on the OpenCensus/OpenTelemetry standard.
Apache Ignite is an excellent tool for external RDBMS, NoSQL or Hadoop database acceleration and offloading. The Ignite in-memory computing platform can power real-time applications that need to process terabytes of data with in-memory speed.
Join us for this webinar to learn about the various Ignite deployment options for database acceleration including:
Join us for a special webinar presented by Branimir Angelov, Co-Founder and CTO of Kubo, Software Architecture Consultant in Obecto, and Member of the Comrade Cooperative.
Over the last decade, the 10x growth of transaction volumes, 50x growth in data volumes, and drive for real-time response and analytics has pushed relational databases beyond their limits. Scaling an existing RDBMS vertically with hardware is expensive and limited. Moving to NoSQL requires new skills and major changes to applications. Ripping out the existing RDBMS and replacing it with another RDBMS with a lower TCO is still risky.