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AWS Elastic Load Balancing VS Apache Ignite

Compare AWS Elastic Load Balancing VS Apache Ignite and see what are their differences

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AWS Elastic Load Balancing logo AWS Elastic Load Balancing

Amazon ELB automatically distributes incoming application traffic across multiple Amazon EC2 instances in the cloud.

Apache Ignite logo Apache Ignite

high-performance, integrated and distributed in-memory platform for computing and transacting on...
  • AWS Elastic Load Balancing Landing page
    Landing page //
    2023-04-27
  • Apache Ignite Landing page
    Landing page //
    2023-07-08

AWS Elastic Load Balancing features and specs

  • Scalability
    AWS Elastic Load Balancing can automatically distribute incoming application traffic across multiple targets, such as Amazon EC2 instances, containers, and IP addresses, promoting application elasticity.
  • Health Monitoring
    It continually checks the health of the registered targets, ensuring that traffic is routed only to healthy instances.
  • Security
    Integrated with AWS's Certificate Manager and Application Load Balancer, allowing easy deployment of SSL/TLS for secure communication.
  • Flexibility
    Supports various types of load balancers: Application, Network, and Classic, each suited to different types of application architectures and requirements.
  • Cost-effective
    Pay-as-you-go pricing model ensures you only pay for the resources you use, which can lead to cost savings compared to a fixed-cost solution.
  • Integration
    Seamlessly integrates with other AWS services such as Auto Scaling, Route 53, CloudWatch, and more for a more robust solution.

Possible disadvantages of AWS Elastic Load Balancing

  • Complexity
    Initial setup and configuration can be complex, especially for users unfamiliar with AWS services and cloud architecture.
  • Cost
    While the pay-as-you-go model is cost-effective, the charges can ramp up quickly, especially for high-traffic applications.
  • Dependence on AWS Ecosystem
    Highly integrated with AWS services, making it less ideal for multi-cloud or hybrid cloud environments.
  • Latency
    In some cases, the load balancer can introduce a slight increase in latency, which might be a concern for latency-sensitive applications.
  • Configuration Limitations
    Some specific configurations and customizations may not be possible, leading to constraints on certain types of applications.

Apache Ignite features and specs

  • In-Memory Data Grid
    Apache Ignite provides a robust in-memory data grid that can drastically improve data access speeds by storing data in memory across distributed nodes.
  • Scalability
    The system is designed to scale horizontally, allowing users to add more nodes to handle increased loads, thereby ensuring high availability and performance.
  • Distributed Compute Capabilities
    Ignite supports parallel execution of tasks across cluster nodes, which is beneficial for complex computations and real-time processing.
  • Persistence
    Although primarily in-memory, Ignite offers a durable and transactional Persistence layer that ensures data can be persisted on disk, providing a hybrid in-memory and persistent storage solution.
  • SQL Queries
    Ignite offers support for ANSI-99 SQL, which allows users to execute complex SQL queries across distributed datasets easily.
  • Integration
    It integrates well with existing Hadoop and Spark setups, allowing users to enhance their existing data pipelines with Ignite’s capabilities.
  • Fault Tolerance
    Apache Ignite includes built-in mechanisms for recovery and ensures that data copies are maintained across nodes for resilience against node failures.

Possible disadvantages of Apache Ignite

  • Complexity
    Apache Ignite can be complex to set up and manage, especially when configuring a large, distributed system with multiple nodes.
  • Resource Intensive
    Running an in-memory data grid like Ignite requires significant memory resources, which can increase operational costs.
  • Learning Curve
    Due to its comprehensive features and distributed nature, there is a steep learning curve associated with effectively utilizing Ignite.
  • Configuration Overhead
    There is substantial configuration overhead involved to optimize performance and ensure proper cluster management.
  • Community Support
    Although it has active development, the community support might not be as robust compared to other more mature solutions, possibly leading to challenges in finding solutions to niche issues.
  • YARN Dependence
    For those looking to integrate with Hadoop, Ignite's optimal performance is sometimes reliant on Hadoop YARN, which can introduce additional complexity.

AWS Elastic Load Balancing videos

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Apache Ignite videos

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Best Practices for a Microservices Architecture on Apache Ignite

More videos:

  • Review - Apache Ignite + GridGain powering up banks and financial institutions with distributed systems

Category Popularity

0-100% (relative to AWS Elastic Load Balancing and Apache Ignite)

AWS Elastic Load Balancing

Apache Ignite

Web Servers
100 100%
Web Servers
0% 0
Databases
0 0%
Databases
100% 100
Web And Application Servers
100 100%
Web And Application Servers
0% 0
NoSQL Databases
0 0%
NoSQL Databases
100% 100

User comments

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Social recommendations and mentions

Based on our record, AWS Elastic Load Balancing should be more popular than Apache Ignite. It has been mentiond 25 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS Elastic Load Balancing mentions (25)

  • Basic AWS Elastic Load Balancer Setup
    Load balancers can be categorized to different types depending on their use cases. On a broader classification, we can divide load balancers into three different categories based on how they are deployed. 1. Hardware load balancers - Dedicated physical appliances designed for high-performance traffic distribution. They are often used by large scale enterprises and data centers that require minimum latency and... - Source: dev.to / 6 months ago
  • Work Stealing: Load-balancing for compute-heavy tasks
    When a backend starts or stops, something needs to update, whether it’s Consul, kube-proxy, ELB, or otherwise. To stop a worker without incurring failures, you need to prevent the load balancer from sending new requests and then finishing existing ones. - Source: dev.to / 10 months ago
  • Load Balancers in AWS
    In this way, you can create a load balancer and custom rules using AWS Elastic Load Balancer. You can refer the official user guide to learn more about load balancing in AWS. - Source: dev.to / 11 months ago
  • A Ride Through Optimising Legacy Spring Boot Services For High Throughput
    Use load balancers and distribute load accordingly to your redundant spring boot services. - Source: dev.to / about 1 year ago
  • DevSecOps with AWS- Ephemeral Environments – Creating test Environments On-Demand - Part 1
    • Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that helps you easily deploy, manage, and scale containerized applications. • AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. AWS Fargate is compatible with both Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic... - Source: dev.to / over 1 year ago
View more

Apache Ignite mentions (3)

  • API Caching: Techniques for Better Performance
    Apache Ignite — Free and open-source, Apache Ignite is a horizontally scalable key-value cache store system with a robust multi-model database that powers APIs to compute distributed data. Ignite provides a security system that can authenticate users' credentials on the server. It can also be used for system workload acceleration, real-time data processing, analytics, and as a graph-centric programming model. - Source: dev.to / 7 months ago
  • Ask HN: P2P Databases?
    Ignite works as you describe: https://ignite.apache.org/ I wouldn't really recommend this approach, I would think more in terms of subscriptions and topics and less of a 'database'. - Source: Hacker News / about 3 years ago
  • .NET and Apache Ignite: Testing Cache and SQL API features — Part I
    Last days, I started using Apache Ignite as a cache strategy for some applications. Apache Ignite is an open-source In-Memory Data Grid, distributed database, caching, and high-performance computing platform. Source: over 3 years ago

What are some alternatives?

When comparing AWS Elastic Load Balancing and Apache Ignite, you can also consider the following products

nginx - A high performance free open source web server powering busiest sites on the Internet.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Traefik - Load Balancer / Reverse Proxy

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Google Cloud Load Balancing - Google Cloud Load Balancer enables users to scale their applications on Google Compute Engine.

memcached - High-performance, distributed memory object caching system

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