ACL Analytics and Snyk compete in the data analytics and security vulnerability sectors. In terms of performance and developer ease, Snyk holds an advantage due to its seamless integrations and extensive database.
Features: ACL Analytics offers superior data control, effective integration with various systems, and error-suggestion capabilities, enhancing audit processes. Snyk provides a simple interface, extensive integrations with cloud systems, and a comprehensive vulnerability database, tailored for developer use.
Room for Improvement: ACL Analytics needs improved ease of use for non-technical users, enhanced visualizations, and better Unicode support. Its scripting options need to be more intuitive, and the pricing model could be more affordable. Snyk can improve its language support, refine reporting and notification systems, and enhance vulnerability filtering. Greater transparency in pricing, especially for add-ons like single sign-on, is necessary.
Ease of Deployment and Customer Service: ACL Analytics deploys across on-premises and hybrid environments, backed by a community but delayed technical support. Snyk's flexible deployment options and strong cloud support are complemented by high customer service ratings, though some onboarding improvements are suggested.
Pricing and ROI: ACL Analytics, although offering significant resource savings and reduced audit hours, faces affordability challenges with its annual pricing model. Snyk's competitive pricing and clear licensing models support developer needs, though costs for additional features like single sign-on might be prohibitive for some.
If an auditor was normally budgeted to take 600 hours, we have implemented a solution to take those audit hours down to 200 hours.
It has proven value in terms of time saving and efficiency, so much so that using open-source tools like Python is not necessary.
This rating is due to slow response times; it would take more than 5 days to respond.
For major technical issues, resolutions typically took six to eight hours.
I escalate many questions to technical support, and they usually respond to me.
Our long-standing association has ensured smooth communication, resulting in favorable support experiences and satisfactory issue resolution.
Their response time aligns with their SLA commitments.
We could understand the implementation of the product and other features without the need for human interaction.
It is a vendor application, and you do not have much power in terms of what we can adjust.
Snyk allows for scaling across large organizations, accommodating tens of thousands of applications and over 60,000 repositories.
I would rate how stable this solution is as a 10.
It didn't take more than half an hour for our IT team to resolve the issue.
I occasionally experience lag when extracting Excel sheets after formulating and setting up the required data.
It would also be beneficial if ACL Analytics included features similar to Tableau for data presentation.
While we had e-learning resources to assist, a more intuitive platform would be beneficial.
We have an issue with the hard coding of passwords in ACL Analytics. You do not have an interface where you can enter a password and then it can be encrypted when you enter it.
It lacks the ability to select branches on its Web UI, forcing users to rely on CLI or CI/CD for that functionality.
The inclusion of AI to remove false positives would be beneficial.
As we are moving toward GenAI, we expect Snyk to leverage AI features to improve code scanning findings.
I would rate the pricing of ACL Analytics as a 10.
ACL Analytics is quite affordable compared to the market.
For example, a thousand dollars last year cost three thousand pounds, but today it is five thousand pounds.
Snyk is recognized as the cheapest option we have evaluated.
After negotiations, we received a special package with a good price point.
Snyk is less expensive.
The most valuable feature of ACL Analytics is its error suggestion capability, where it indicates problems if operations are incorrect.
With over a million clients, this feature helps tremendously in identifying fraud detection in client accounts.
I can access data from various sources, both relational and non-relational databases, using one tool.
Our integration of Snyk into GitHub allows us to automatically scan codebases and identify issues, which has improved efficiency.
Snyk helps detect vulnerabilities before code moves to production, allowing for integration with DevOps and providing a shift-left advantage by identifying and fixing bugs before deployment.
The best feature of Snyk is the integration with our ticketing system, which is Jira.
| Product | Market Share (%) |
|---|---|
| ACL Analytics | 2.9% |
| Snyk | 1.4% |
| Other | 95.7% |
| Company Size | Count |
|---|---|
| Small Business | 1 |
| Midsize Enterprise | 2 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 9 |
| Large Enterprise | 21 |
Snyk excels in integrating security within the development lifecycle, providing teams with an AI Trust Platform that combines speed with security efficiency, ensuring robust AI application development.
Snyk empowers developers with AI-ready engines offering broad coverage, accuracy, and speed essential for modern development. With AI-powered visibility and security, Snyk allows proactive threat prevention and swift threat remediation. The platform supports shifts toward LLM engineering and AI code analysis, enhancing security and development productivity. Snyk collaborates with GenAI coding assistants for improved productivity and AI application threat management. Platform extensibility supports evolving standards with API access and native integrations, ensuring comprehensive and seamless security embedding in development tools.
What are Snyk's standout features?Industries leverage Snyk for security in CI/CD pipelines by automating checks for dependency vulnerabilities and managing open-source licenses. Its Docker and Kubernetes scanning capabilities enhance container security, supporting a proactive security approach. Integrations with platforms like GitHub and Azure DevOps optimize implementation across diverse software environments.
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