GITNUXSOFTWARE ADVICE
SecurityTop 10 Best Bouncer Software of 2026
Top 10 Bouncer Software ranked for protection, performance, and rules, including Akamai, Cloudflare, and AWS WAF for technical teams.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Akamai Enterprise Web Application Firewall
Managed WAF rules enforced at Akamai’s edge with Bot Management integration
Built for enterprises protecting APIs and web apps at the edge with skilled security teams.
Cloudflare Web Application Firewall
Editor pickManaged WAF rules with adaptive security signals that apply at the Cloudflare edge
Built for teams protecting public web apps and APIs with edge-enforced policies.
AWS WAF
Editor pickManaged rule groups with bot and common threat protection
Built for aWS-centric teams needing configurable web ACLs for apps and APIs.
Related reading
Comparison Table
This comparison table evaluates Bouncer Software tools used for web application firewall and bot mitigation, focusing on integration depth, data model, and how rules and signatures map into each vendor's schema. It also compares automation and API surface for provisioning and change control, plus admin and governance controls such as RBAC and audit log coverage. The rankings track protection effectiveness, throughput impact, and rule expressiveness across Akamai, Cloudflare, AWS, Azure, Google Cloud, and other included platforms.
Akamai Enterprise Web Application Firewall
edge WAFProvides web application firewall controls that filter and block malicious traffic at the edge using managed attack signatures and policy rules.
Managed WAF rules enforced at Akamai’s edge with Bot Management integration
Akamai Enterprise Web Application Firewall inspects API and web traffic at the edge using Akamai threat intelligence and Bot Management signals. It applies OWASP-aligned rule logic with both signature-style detections and behavioral controls, then enforces those decisions through configurable policies. The platform fits environments where traffic must be filtered consistently across multiple domains and application entry points.
A key tradeoff is that policy tuning and false-positive management require careful staging because behavioral controls can depend on application and traffic baselines. A strong usage situation is protecting externally exposed APIs and web forms when multiple teams deploy frequent changes and need centralized enforcement at the network edge.
- +Edge-distributed enforcement reduces latency for high-volume web traffic
- +Strong coverage for OWASP attack patterns with managed security rules
- +Bot signals improve protection against scraping, credential stuffing, and automation
- –Policy tuning requires security expertise and careful change management
- –Debugging false positives can be slower across distributed rule sets
- –Integrations and deployment patterns can add operational complexity
Security engineering teams
Edge enforcement for OWASP web attacks
Reduced exploit attempts at edge
API platform owners
Protect public endpoints with behavioral checks
Fewer malicious API calls
Show 2 more scenarios
SOC and threat operations
Use Bot Management signals for triage
Faster triage for active attacks
They correlate bot and attack indicators to prioritize incident response for suspicious sessions and traffic.
Global delivery teams
Uniform controls across multi-domain apps
Consistent protection at scale
They maintain consistent WAF enforcement across regions and domains while routing requests through Akamai.
Best for: Enterprises protecting APIs and web apps at the edge with skilled security teams
More related reading
Cloudflare Web Application Firewall
cloud WAFDelivers managed WAF protections with configurable firewall rules that inspect HTTP requests and block common web attacks.
Managed WAF rules with adaptive security signals that apply at the Cloudflare edge
Cloudflare Web Application Firewall inspects HTTP requests at the edge using configurable WAF rules and managed protections for frequent attack patterns like SQL injection and cross-site scripting. It ties enforcement to request attributes, including headers, cookies, and paths, so blocks can occur before traffic reaches origin servers. Managed threat intelligence updates feed into rule evaluation and bot filtering signals so decisions reflect current attacker behavior.
A tradeoff is that strict rules can increase false positives for custom apps with unusual request formats, which requires tuning in the WAF rule set. It fits best for teams running websites and APIs behind Cloudflare that need consistent protection across many locations while centralizing security controls in one policy layer.
- +Edge inspection blocks malicious requests before they reach origin servers.
- +Managed WAF rules cover common OWASP-style attack patterns.
- +Granular rule logic supports host, path, header, and IP-based conditions.
- –Complex rule tuning can be time-consuming for multi-application environments.
- –Misconfigured exclusions and overrides can weaken protections during incidents.
- –Advanced troubleshooting requires understanding Cloudflare event logs and caching layers.
Security engineers for APIs
Block injection and traversal at edge
Reduced exploit attempts
Platform teams with global traffic
Enforce uniform rules across regions
Consistent security posture
Show 2 more scenarios
App teams handling high bot traffic
Filter bots using request signals
Lowered abusive traffic
Bot filtering signals feed into the request lifecycle to limit automated abuse.
Incident responders
Respond to emerging threats fast
Faster mitigation cycles
Managed threat intelligence updates change enforcement without redeploying application code.
Best for: Teams protecting public web apps and APIs with edge-enforced policies
AWS WAF
managed WAFFilters web requests using rules that match IP reputation, rate limits, and threat signatures before traffic reaches applications.
Managed rule groups with bot and common threat protection
AWS WAF distinguishes itself by integrating rule-based web protection directly into AWS edge and load balancer layers. It supports managed rule sets, custom match conditions, and scripted request inspection patterns for controlling access to web applications and APIs.
Core capabilities include IP and geo blocking, rate limiting, bot mitigation, and association with CloudFront, Application Load Balancer, and API Gateway. Event-driven visibility comes via CloudWatch metrics and sampled request logs for operational tuning.
- +Managed rule groups cover common exploits like SQLi and XSS without custom rule authoring
- +Granular match conditions include IP, headers, URI paths, query strings, and HTTP body inspection
- +Rate-based rules reduce abusive bursts by tracking request volume per client
- +CloudWatch metrics and sampled requests support iterative rule tuning
- –Rule debugging can be slow due to many overlapping conditions and priorities
- –Advanced bot and inspection logic often requires careful tuning to avoid false positives
- –Deploying consistent rules across multiple entry points adds operational overhead
Security operations teams
Reduce web exploits at AWS edge
Fewer successful attack attempts
Platform engineers
Control API access through AWS WAF
Stabilized API request volume
Show 1 more scenario
Incident response teams
Investigate sampled requests during incidents
Faster containment decisions
Teams correlate CloudWatch metrics and sampled logs to validate rule effectiveness and scope impact.
Best for: AWS-centric teams needing configurable web ACLs for apps and APIs
More related reading
Azure Web Application Firewall
managed WAFProtects web apps by applying managed and custom WAF rules to block malicious requests at the application gateway layer.
Managed rule sets with granular overrides and custom rule additions within a WAF policy
Azure Web Application Firewall protects web apps in front of the HTTP pipeline using configurable managed rules and custom WAF policies. It supports detection and mitigation for common OWASP risks with pattern-based signatures and rule groups that can be scoped to sites and routes. Integrations with Azure Monitor and log analytics make it possible to track blocked and allowed requests and tune policies from observed traffic.
- +Managed rule sets cover OWASP-style attack patterns with minimal rule authoring
- +Custom rules allow header, URL path, query string, and IP-based matching
- +Centralized policy scoping controls enforcement at app and route granularity
- +Detailed logs show matched rules, actions taken, and request metadata
- –Tuning false positives requires careful observation and iterative policy changes
- –Complex custom match conditions can become harder to maintain at scale
- –Multi-layer deployments add operational complexity across network resources
Best for: Azure-centric teams needing managed and custom WAF protection with strong observability
Google Cloud Armor
network edge protectionImplements security policy enforcement on load balancers to stop volumetric attacks and block malicious request patterns.
Adaptive protection with managed rule sets plus custom rules at the Google edge
Google Cloud Armor distinctively combines WAF and DDoS protection directly with Google Cloud load balancers and global edge routing. It enforces security policies with managed rule sets, custom rules, and geo, IP, and protocol match conditions. It also supports rate limiting, bot mitigation signals, and logging hooks for investigating blocked traffic and attack patterns.
- +Managed rule sets cover common WAF use cases without building signatures
- +Custom policy rules support IP, geo, protocol, and header conditions
- +Rate limiting helps reduce abuse and protects origin services
- +Works natively with Google Cloud load balancers for consistent enforcement
- –Rule debugging can be slow when multiple conditions interact
- –Advanced tuning requires careful ordering and testing across environments
- –Limited portability for non Google Cloud load balancer architectures
Best for: Teams securing Google Cloud apps with WAF, DDoS controls, and managed rules
Imperva Cloud WAF
virtual patching WAFSecures web applications with virtual patching and managed WAF rules that mitigate OWASP-style threats.
Managed WAF rules with automated threat detection and policy enforcement
Imperva Cloud WAF stands out with centralized, cloud-delivered web application protection that can be applied across environments through consistent policy controls. It provides signature and ruleset based threat detection plus managed protections for common web attacks like OWASP Top 10 classes.
Traffic inspection supports bot and API oriented protections, and the platform offers logging and reporting for security visibility. Deployment is designed for quick cutover using network and application configuration rather than agents.
- +Strong managed WAF protections with broad attack coverage
- +Centralized policy management helps keep protections consistent
- +Good telemetry for security investigations and rule tuning
- –Advanced tuning for complex apps can take time and expertise
- –Migration from existing WAF policies may require careful validation
- –Context for false positives often depends on detailed log analysis
Best for: Teams securing public web apps and APIs with managed WAF policies
More related reading
Fortinet FortiWeb
appliance WAFProvides an application layer security appliance and virtual platform that detects and blocks web attacks using WAF and bot protections.
FortiWeb web application firewall and bot detection operating at the reverse-proxy layer
Fortinet FortiWeb stands out as a security gateway that combines web application firewall and bot detection to reduce web-facing attacks at the edge. It provides policy-driven protection for common application threats like OWASP Top categories, credential abuse, and automated scraping.
Its integration with Fortinet security fabric helps coordinate logs and threat intelligence across adjacent Fortinet products. Operationally, it is strongest for teams that want centralized ingress control for web apps rather than lightweight, user-managed bouncer logic.
- +Web attack mitigation with signature and policy controls
- +Bot detection supports automated abuse and scraping patterns
- +Integrates with Fortinet security fabric for coordinated visibility
- –Complex policy tuning is required to reduce false positives
- –Best results depend on accurate traffic and application baselining
- –Deployment and ongoing management demand security engineering effort
Best for: Enterprises needing managed web app edge protection for busy public apps
Radware AppWall
WAF and DDoSProtects web and application services with WAF capabilities designed to mitigate attacks and maintain application availability.
Positive validation and runtime enforcement via AppWall security policies
Radware AppWall stands out with an application-layer security approach that targets web app abuse through enforced policies at runtime. It focuses on positive validation and bot and attack mitigation patterns for HTTP traffic, including selective protection by application path. It also supports integration with existing security stacks for visibility and policy enforcement.
- +Runtime application-layer enforcement using positive validation
- +Strong coverage for web abuse patterns and HTTP request shaping
- +Policy granularity by application and request attributes
- +Designed to integrate into broader security tooling pipelines
- –Policy tuning can be complex for large, dynamic application sets
- –Less suitable for non-web workloads and transport-level filtering
- –Tight enforcement increases false-positive risk if baselines are weak
- –Operational overhead grows as protected surface area expands
Best for: Enterprises protecting critical web apps needing runtime policy enforcement
More related reading
Sucuri Web Application Firewall
website securityOffers website security with malware scanning and a WAF that blocks suspicious requests targeting web endpoints.
Managed WAF with automated rule management and security reporting
Sucuri Web Application Firewall centers on protecting web apps through managed WAF rules, malware cleaning, and incident-oriented monitoring. It combines traffic filtering with security tooling like file integrity checks and website security reporting to support both prevention and response workflows.
Configuration relies on domain onboarding and policy settings rather than custom application code changes. The solution fits teams needing centralized defenses for multiple sites with ongoing security visibility.
- +Managed WAF rules cover common OWASP attack patterns with low maintenance
- +Security monitoring and reporting support faster investigation and confirmation of blocks
- +File integrity checks help detect unauthorized changes tied to web compromises
- –Tuning false positives can require iterative policy adjustments per application
- –Advanced protections may feel less customizable than self-managed WAF stacks
- –Operational visibility is strong, but playbook guidance for custom incidents is limited
Best for: Teams securing public websites that need managed WAF plus integrity monitoring
Sucuri Firewall for Websites
web firewallProvides a website firewall and monitoring workflow that helps stop malicious traffic and supports incident investigation.
SiteCheck malware and blacklist status reporting with security header and configuration checks
Sucuri Firewall for Websites stands out by combining a preflight site security check with actionable hardening guidance via sitecheck.sucuri.net. The sitecheck workflow inspects a domain for malware signals, blacklisting status, security headers, and common configuration exposures.
It also surfaces plugin and theme risk indicators tied to WordPress style components and outdated elements. The result is a bouncer-style intake that turns scan findings into next steps for blocking threats before they become incidents.
- +Clear site health breakdown covering malware, blacklists, and security headers
- +Action-oriented guidance links findings to concrete remediation categories
- +Fast, URL-based scanning works without deploying an agent or script
- –Report depth is limited compared to full continuous firewall telemetry
- –Some recommendations require manual verification and hosting-level changes
- –Not a substitute for server-side logging, WAF rules, and monitoring
Best for: Teams needing quick pre-deployment security triage for web domains
Conclusion
After evaluating 10 security, Akamai Enterprise Web Application Firewall stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Bouncer Software
This buyer’s guide covers web application firewall and edge-request filtering tools including Akamai Enterprise Web Application Firewall, Cloudflare Web Application Firewall, AWS WAF, Azure Web Application Firewall, Google Cloud Armor, Imperva Cloud WAF, Fortinet FortiWeb, Radware AppWall, Sucuri Web Application Firewall, and Sucuri Firewall for Websites.
It focuses on integration depth, data model, automation and API surface, and admin and governance controls across edge and gateway enforcement patterns so selection decisions stay tied to concrete mechanisms like rule evaluation, policy scoping, and logging workflows.
Recommendations connect protection coverage, performance behavior, and rule-management overhead to named capabilities such as managed rule groups, runtime positive validation, and load balancer native enforcement.
Edge and gateway policy enforcement that blocks malicious HTTP requests
Bouncer software in this guide enforces allow or block decisions on inbound web and API traffic by applying WAF and bot-aware rule sets at the edge, gateway, or runtime request layer.
Tools like Cloudflare Web Application Firewall and AWS WAF match requests using attributes such as headers, paths, cookies, IP reputation, and rate signals, then block before origin services handle the request.
Akamai Enterprise Web Application Firewall shows how centralized rule logic at the edge can combine managed OWASP-style detections with Bot Management signals for credential abuse and scraping resistance.
Evaluation criteria for integration, data model control, and governed automation
Integration depth determines whether WAF decisions can be consistently enforced across multiple entry points such as load balancers, API gateways, and global edge routes.
Automation and API surface determine how fast policies can be provisioned, how reliably rule changes can be promoted across environments, and how programmatic governance can attach to configuration changes.
Admin and governance controls determine how RBAC, scoping, and audit-style operational visibility support safe tuning when false positives or incident response actions occur.
Managed WAF rule sets enforced at the edge
Akamai Enterprise Web Application Firewall and Cloudflare Web Application Firewall both enforce managed WAF protections at the edge with rule evaluation driven by OWASP-aligned patterns for SQL injection and cross-site scripting. AWS WAF and Google Cloud Armor add managed rule groups that reduce custom signature burden by covering common threats without requiring bespoke rule authoring for every exploit pattern.
Bot-aware signals tied to request evaluation
Akamai Enterprise Web Application Firewall integrates Bot Management signals into its edge rule enforcement, which improves protection against scraping and credential stuffing. Fortinet FortiWeb adds bot detection at the reverse-proxy layer so web attack mitigation can incorporate automated abuse patterns before they reach application logic.
Policy scoping and granular match conditions
Azure Web Application Firewall supports managed and custom WAF policies with rule scoping by sites and routes, plus custom matching on header, URL path, query string, and IP attributes. Cloudflare Web Application Firewall provides granular rule logic using host, path, header, and IP-based conditions so blocks can target specific request shapes without weakening global posture.
Runtime positive validation for application-layer enforcement
Radware AppWall focuses on positive validation and runtime application-layer enforcement, which reduces reliance on signature-style matching by shaping and validating HTTP requests per application path. This runtime approach pairs well with strong baseline expectations because tight enforcement can increase false-positive risk when baselines are weak.
Visibility for rule tuning and incident workflows
AWS WAF ties operational visibility to CloudWatch metrics and sampled request logs, which supports iterative tuning of match conditions and rule priorities. Azure Web Application Firewall and Cloudflare Web Application Firewall also rely on logs and event records that show matched rules and actions, which helps identify why a request was blocked during debugging.
Operational rollout patterns that reduce agent reliance
Imperva Cloud WAF emphasizes policy controls that can be applied across environments with centralized management and quick cutover using network and application configuration rather than agent deployment. Akamai Enterprise Web Application Firewall and Sucuri Web Application Firewall also fit scenarios where managed defenses need consistent behavior across multiple domains with low per-host operational work.
Choose a tool by aligning enforcement location, governance needs, and rule-change workflow
First map enforcement location to traffic topology so rules run where latency, coverage, and routing decisions actually happen.
Second map rule-change workflow to governance expectations so policy updates can be provisioned, tested, and tracked with enough operational visibility to handle false positives and incident response.
Third check how the tool’s data model expresses policy logic so match conditions align with application routing and request formats.
Pick enforcement placement based on edge, load balancer, or runtime needs
If enforcement must happen before traffic reaches origins across many networks, pick edge-distributed platforms such as Akamai Enterprise Web Application Firewall and Cloudflare Web Application Firewall. If enforcement must integrate tightly with AWS networking primitives, choose AWS WAF with associations to CloudFront, Application Load Balancer, and API Gateway.
Match the policy data model to how requests vary across hosts and routes
Use Azure Web Application Firewall when policies must be scoped at site and route granularity and custom rules must match headers, URL paths, query strings, and IP attributes. Use Cloudflare Web Application Firewall when request blocking needs host, path, header, and IP conditions with managed threat intelligence updates feeding rule evaluation.
Confirm automation and extensibility paths for rule provisioning and tuning
Prefer tools that can drive rule sets through programmatic configuration workflows and operational logs, which is central to safe promotion of managed WAF policies like those in AWS WAF and Google Cloud Armor. If runtime request shaping is required, use Radware AppWall positive validation policies to enforce HTTP request correctness per application path rather than relying only on signatures.
Require governance-grade observability for incident debugging and audit trails
Select AWS WAF when CloudWatch metrics and sampled request logs are needed to tune overlapping conditions and priorities without losing operational context. Select Azure Web Application Firewall and Cloudflare Web Application Firewall when event logs must show matched rules, actions taken, and request metadata for faster false-positive debugging.
Align bot mitigation strategy to expected abuse patterns
Choose Akamai Enterprise Web Application Firewall when Bot Management signals are a required input to managed WAF decisions for scraping and credential abuse. Choose Fortinet FortiWeb when a reverse-proxy gateway model with integrated bot detection fits existing Fortinet security fabric logging and threat intelligence coordination.
Teams and environments that benefit from specific enforcement models
Bouncer software selection depends on where requests enter the environment and how change governance works across teams.
Different tools optimize for edge consistency, cloud-native integration, runtime validation, or incident-oriented triage rather than only for broad threat coverage.
The right choice becomes clear once protection coverage, performance behavior, and rule-management overhead are mapped to each audience’s operational model.
Enterprise security teams centralizing edge enforcement for multi-domain APIs and web apps
Akamai Enterprise Web Application Firewall fits because managed OWASP-style WAF rules run at Akamai’s edge with Bot Management integration for scraping and credential stuffing. This model also supports consistent enforcement across multiple application entry points when security teams can manage policy tuning and staging.
Cloud and network teams standardizing WAF policies across global traffic in one control plane
Cloudflare Web Application Firewall fits because managed WAF rules and adaptive security signals evaluate HTTP requests at the edge using headers, cookies, and path attributes. This also suits teams that want centralized policy control across many locations while accepting that custom app formats require careful rule tuning.
AWS-native teams that need web ACL control bound to AWS services
AWS WAF fits because it associates managed rule groups with CloudFront, Application Load Balancer, and API Gateway while providing CloudWatch metrics and sampled request logs. This supports governance for rule tuning when debugging overlapping conditions and rate-based behavior is part of operations.
Azure-centric teams requiring route-level scoping and observability in Azure monitoring tools
Azure Web Application Firewall fits because it supports managed and custom WAF policies with granular overrides and custom rule additions scoped to sites and routes. Integrations with Azure Monitor and log analytics make blocked and allowed request tracking actionable for iterative tuning.
Enterprises that need runtime request correctness checks for critical web applications
Radware AppWall fits because it uses positive validation and runtime enforcement with policy granularity by application path. It supports environments where application baselines can be established and maintained to reduce false-positive risk.
Where WAF policy projects fail and how specific tools help avoid the trap
Most failures come from mismatched policy logic to request formats, insufficient observability for debugging, or deployment patterns that create inconsistent enforcement across entry points.
False positives also become operationally expensive when governance and change management are not built into the rule promotion workflow.
These mistakes show up across managed WAF and runtime validation approaches in different ways.
Treating managed WAF as plug-and-play without staging for tuning
Akamai Enterprise Web Application Firewall and Cloudflare Web Application Firewall both require careful staging because behavioral controls and adaptive signals depend on traffic baselines. Corrective action is to run rule changes through a controlled promotion workflow and use the tools’ logs to validate matched rules and actions before broad rollout.
Building exclusions that weaken protections during incident response
Cloudflare Web Application Firewall calls out that misconfigured exclusions and overrides can weaken protections during incidents. Corrective action is to restrict overrides to specific hosts or paths using granular rule logic and to rely on event logs to confirm the override scope.
Debugging slow overlap in rule priorities and conditions
AWS WAF can make rule debugging slow when many overlapping conditions and priorities interact. Corrective action is to use CloudWatch metrics and sampled request logs to isolate which match criteria triggered a block and then adjust priorities or match conditions.
Selecting runtime positive validation without stable request baselines
Radware AppWall can increase false-positive risk when tight enforcement runs against weak baselines for critical application flows. Corrective action is to limit runtime enforcement scope by application path first and then expand coverage only after request shaping and positive validation rules stabilize.
Choosing site triage workflows that cannot replace continuous enforcement
Sucuri Firewall for Websites emphasizes preflight site security checks using sitecheck data and hardening guidance, but it is not a substitute for server-side logging and continuous WAF rules. Corrective action is to use Sucuri Web Application Firewall for ongoing managed WAF enforcement and pair it with integrity monitoring for investigation and response workflows.
How We Selected and Ranked These Tools
We evaluated Akamai Enterprise Web Application Firewall, Cloudflare Web Application Firewall, AWS WAF, Azure Web Application Firewall, Google Cloud Armor, Imperva Cloud WAF, Fortinet FortiWeb, Radware AppWall, Sucuri Web Application Firewall, and Sucuri Firewall for Websites on feature coverage, ease of use, and value.
Each tool received an overall rating as a weighted average where features carry the most weight, and ease of use and value each contribute substantially to the final ordering.
This scoring reflects criteria-based editorial research rather than hands-on lab testing.
Akamai Enterprise Web Application Firewall stood apart because managed WAF rules enforced at Akamai’s edge with Bot Management integration combined a very high features score with strong ease of use and value, which lifted it across protection coverage and operational tuning expectations.
Frequently Asked Questions About Bouncer Software
How does Bouncer Software differ from an edge WAF when the goal is API and web request filtering?
Which tools provide rules and automation that can be expressed through an API or integration workflow?
What are the tradeoffs of centralized policy enforcement across multiple domains compared with per-application logic?
How do SSO and admin RBAC requirements affect operational access control for bouncer-style policies?
What data model and schema mapping challenges appear during data migration from an existing access-control system?
How do audit logs and sampled request visibility help debug why a rule blocks traffic?
Which environments benefit most from bot-aware enforcement at the reverse-proxy or load balancer layer?
What workflow fits organizations that need pre-deployment triage before a domain goes live?
How do teams handle false positives when WAF or bouncer rules become strict for custom request formats?
Tools reviewed
Primary sources checked during evaluation.
akamai.comaws.amazon.comReferenced in the comparison table and product reviews above.
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