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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GridGain Control Center is a comprehensive troubleshooting, management and monitoring solution for Apache Ignite and the GridGain platform. While Apache Ignite and the GridGain platform can enable building high-performance and scalability applications, troubleshooting and monitoring distributed clusters can be tricky.
Join us for a presentation by Greg Stachnick, Director of Product Management for Control Center to lear learn how Control Center simplifies key troubleshooting tasks, watch technical demos, and learn about the new Control Center SaaS subscription options.
Running Apache Ignite on Kubernetes can help Ignite developers streamline deployment and management of applications in cloud environments, both private and public. Apache Ignite is Kubernetes-friendly with features that simplify cluster provisioning and minimize the operational and management burden.
In the webinar, Colin will introduce the capabilities of the joint Ignite and Kubernetes solution and demo how set up Apache Ignite with Kubernetes quickly and reliably. Topics covered include:
The latest Apache Ignite release includes many new features, such as expanded thin client support, improved cluster monitoring, and enhanced cluster self-tuning. Join Vladimir as he discusses and demonstrates the key improvements that Apache Ignite 2.10 offers:
Spring is a popular framework, and Apache Ignite is a fast layer for data storage. Adding Ignite enables you to manage http sessions, cache-application data, and so on. During this 1.5 hour session, Semyon uses the Spring framework to create a simple web application and demonstrates how Apache Ignite can empower the application. He walks you through steps such as the following:
- Adding authorization to the application
- Using Spring to store the data solution
- Configuring Apache Ignite to increase the application’s durability
Apache Ignite’s ANSI-99 SQL support provides application developers a classical SQL database experience while enabling in-memory speeds at a petabyte scale for a variety of workloads. Concise SQL syntax and availability of JDBC and ODBC drivers shields the complexity of Ignite’s distributed architecture from developers and allows them to easily manage and query distributed datasets.
Nevertheless, you should consider using a few essential tools and techniques to optimize SQL queries when faced with slow or stuck queries, OutOfMemoryException errors, or incorrect results.
The latest release of the GridGain in-memory computing platform features enhanced support for the platform’s multi-tier database engine, that scales up and out across memory and disk. The changes enable customers to leverage the disk tier of the database engine to query much larger data sets, reduce cost of ownership, and secure sensitive or personal data at rest. Companies can use GridGain for a greater number of production use cases, ranging from complex real-time analytics to mission-critical transactional workloads
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.
GridGain Nebula, a managed services offering (MSO) for Apache Ignite and GridGain, can offload the management of your in-memory computing environment to provide maximum reliability at a fraction of the cost of staffing an internal team. This allows your organization to focus on developing applications built on GridGain or Ignite without requiring an internal IT team to manage your in-memory computing environment.
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 workshop, Alexey discusses the following topics:
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.
Apache Ignite’s ANSI-99 SQL support provides application developers a classical SQL database experience while enabling in-memory speeds at a petabyte scale for a variety of workloads. Concise SQL syntax and availability of JDBC and ODBC drivers shields the complexity of Ignite’s distributed architecture from developers and allows them to easily manage and query distributed datasets.
Nevertheless, you should consider using a few essential tools and techniques to optimize SQL queries when faced with slow or stuck queries, OutOfMemoryException errors, or incorrect results.
The latest release of the GridGain in-memory computing platform features enhanced support for the platform’s multi-tier database engine, that scales up and out across memory and disk. The changes enable customers to leverage the disk tier of the database engine to query much larger data sets, reduce cost of ownership, and secure sensitive or personal data at rest.
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 workshop, 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
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:
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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.