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    GridGain In-Memory Computing Platform - Enterprise Edition

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    Deployed on AWS
    The GridGain(R) In-Memory Computing Platform, built on Apache(R) Ignite(TM), enables you to dramatically accelerate and scale out your data-intensive applications without ripping and replacing your existing databases.

    Overview

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    The GridGain(R) In-Memory Computing Platform, built on Apache(R) Ignite(TM), enables you to dramatically accelerate and scale out your data-intensive applications without ripping and replacing your existing databases. GridGain delivers massive scalability and tremendous speed, managing data from multiple databases. Query times are up to 1,000x faster than systems built on disk-based databases. You can easily scale out your GridGain instance to support petabytes of in-memory data by adding new nodes to your cluster. GridGain includes an in-memory data grid, in-memory database, streaming analytics, and a continuous learning framework.

    You can modernize your data-intensive architecture by inserting GridGain between your existing application and data layers. GridGain works seamlessly with RDBMS, NoSQL and Hadoop databases. It features a unified API which supports SQL, C++, .NET, PHP, MapReduce, JAVA/Scala/Groovy, and Node.js access for the application layer. GridGain can run on premises, in a hybrid environment, or on the AWS or other public cloud platforms.

    Highlights

    • The GridGain(R) In-Memory Computing Platform, built on Apache(R) Ignite(TM), enables you to dramatically accelerate and scale out your data-intensive applications without ripping and replacing your existing databases.
    • GridGain(R) delivers unlimited scalability and tremendous speed. Query times are up to 1,000x faster than systems built on disk-based databases. You can easily scale out your GridGain instance to support petabytes of in-memory data by adding new nodes to your cluster.
    • GridGain(R) modernizes your data-intensive applications. GridGain works seamlessly with RDBMS, NoSQL and Hadoop databases. It features a unified API which supports SQL, C++, .NET, PHP, MapReduce, JAVA/Scala/Groovy, and Node.js.

    Details

    Delivery method

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    64-bit (x86) Amazon Machine Image (AMI)

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    Operating system
    AmazonLinux 2.0

    Deployed on AWS

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    Pricing

    GridGain In-Memory Computing Platform - Enterprise Edition

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (37)

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    Dimension
    Cost/hour
    c4.xlarge
    Recommended
    $1.50
    c3.xlarge
    $1.50
    d2.xlarge
    $1.50
    m4.10xlarge
    $15.00
    i2.xlarge
    $1.50
    r3.2xlarge
    $3.00
    m3.xlarge
    $1.50
    r3.4xlarge
    $6.00
    m4.xlarge
    $1.50
    m3.2xlarge
    $3.00

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    Usage information

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    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

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    15 external reviews
    Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
    Information Technology and Services

    Powerful In-Memory Computing Platform with Strong Performance

    Reviewed on Jul 28, 2025
    Review provided by G2
    What do you like best about the product?
    GridGain offers exceptional in-memory data grid capabilities that significantly improve application performance. The integration with existing Java code is smooth, and the support for distributed caching and real-time analytics is excellent. I also appreciate the robust scalability features and support for SQL queries.
    What do you dislike about the product?
    The learning curve is steep, especially for newcomers to distributed systems. The documentation, while extensive, could benefit from more hands-on examples and clearer navigation. Also, some configuration aspects feel overly complex and require deep technical knowledge.
    What problems is the product solving and how is that benefiting you?
    GridGain helps reduce latency for high-volume, data-intensive applications. It solves performance bottlenecks by enabling in-memory data access and processing, leading to faster analytics and real-time decision-making in critical systems.
    Alaa M.

    Supercharged Data Access for Smarter, Faster Strategy

    Reviewed on Jul 28, 2025
    Review provided by G2
    What do you like best about the product?
    The speed. GridGain genuinely changes how fast you can access and act on data. For someone in a strategic role, that’s a game-changer. You can get real-time answers and model scenarios on the go.
    What do you dislike about the product?
    The learning curve was a bit steep at first. It’s not plug-and-play, we needed support to get everything integrated properly, if your backend is outdated, you might not unlock the full benefits immediately cause it does require a well structured architecture if you will.
    What problems is the product solving and how is that benefiting you?
    It's mainly helping me access data quickly so no more delays in forecasting or decision-making, plus it helped getting a unified view for different departments thus allowing us to pivot scenarios much quicker than before.
    youssif t.

    High-Performance In Memory Computing

    Reviewed on Jul 28, 2025
    Review provided by G2
    What do you like best about the product?
    its exceptional in-memory computing performance and real-time processing capabilities. It allows for lightning-fast data access and distributed computation, which significantly improves the performance of applications dealing with large-scale transactional and analytical workloads. The platform’s support for standard SQL and seamless integration with existing databases makes it highly practical for enterprise environments.
    What do you dislike about the product?
    it offers outstanding performance, it comes with a steep learning curve and can be complex to set up and configure. Initial deployment requires in-depth technical expertise, especially when tuning memory usage and configuring clusters for optimal performance.
    What problems is the product solving and how is that benefiting you?
    solves the problem of slow data access and processing in high-throughput environments by enabling in-memory data storage and distributed computing.
    Information Technology and Services

    Powerful In-Memory Computing for High-Performance Apps

    Reviewed on Jul 26, 2025
    Review provided by G2
    What do you like best about the product?
    GridGain stands out for its speed, particularly for real-time, large-scale data processing. I have been impressed with its distributed in-memory data grid, which really speeds up any applications. The SQL support over the in-memory store has been particularly useful and the integration with the existing databases has been seamless.
    What do you dislike about the product?
    GridGain is a powerful tool but the learning curve is very steep since getting it set up in a more complex environment is difficult. The documentation can definitely be geared to new users better. It also takes quite a long time to configure and tune it initially, which may or may not be suited to teams with little background in distributed systems.
    What problems is the product solving and how is that benefiting you?
    GridGain provides me with the solution I am looking for to offload my processing of large amounts of data with low latency. It gives me an in-memory data layer, which speeds up application response times, and therefore user experience. Additionally, it decreases load on traditional databases.
    Motawea N.

    GridGain Delivers Real-Time Power for Data-Driven Applications

    Reviewed on Jul 23, 2025
    Review provided by G2
    What do you like best about the product?
    What I like best about GridGain is its seamless combination of in-memory speed with distributed scalability and enterprise-grade features.
    What do you dislike about the product?
    What I dislike about GridGain—or where it can fall short—includes the following:

    Steep Learning Curve:
    The architecture is powerful but complex. New users often struggle with concepts like data affinity, collocated processing, and distributed joins.

    Heavyweight Compared to Simple Caches:
    For basic caching needs, GridGain (and Ignite) can feel like overkill compared to lightweight solutions like Redis or Memcached.

    Advanced Features Behind Paywall:
    Many enterprise features (security, monitoring, rolling upgrades) are only in the Enterprise or Ultimate editions, not in the Community Edition.

    GridGain is powerful, but its complexity, configuration overhead, and limited free-tier features can be barriers to adoption.
    What problems is the product solving and how is that benefiting you?
    GridGain solves several critical problems in high-performance data processing, especially in distributed, real-time environments. Here's a breakdown of the main problems it addresses and how they benefit you:

    Problem: Slow Data Access from Disk-Based Databases
    Traditional databases are too slow for real-time apps due to disk I/O latency.
    GridGain Benefit:
    Stores data in-memory across a cluster for microsecond response times, enabling real-time analytics, fraud detection, and responsive user experiences.

    Problem: Scaling Bottlenecks in Centralized Systems
    Single-node systems can't handle growing data and user load efficiently.
    GridGain Benefit:
    Its distributed architecture scales horizontally, letting you add nodes as demand grows, ensuring high availability and elasticity.

    Problem: Separation of OLTP and OLAP Systems (HTAP Gap)
    Using different systems for transactions and analytics creates latency, duplication, and complexity.
    GridGain Benefit:
    Supports Hybrid Transactional/Analytical Processing (HTAP), so you can query live transactional data in real time, reducing architecture complexity.

    GridGain solves performance, scalability, and latency issues in data-intensive systems, enabling real-time processing and simplifying complex architectures.
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