Datadog and Logpoint are both significant players in the monitoring and SIEM markets. Datadog seems to have the upper hand due to its extensive integration capabilities and comprehensive observability features.
Features: Datadog provides extensive integrations, seamless transition from metrics to alerts, and a robust ecosystem, making it ideal for cloud-based environments. Logpoint focuses on log collection and analysis, providing essential SIEM capabilities but lacking the breadth of integrations found in Datadog.
Room for Improvement: Datadog needs more user-friendly metrics, advanced filtering, and a transparent pricing model. Logpoint should enhance its UI, incorporate advanced security features, and modernize its deployment options to improve flexibility and compatibility with cloud-native solutions.
Ease of Deployment and Customer Service: Datadog offers easy deployment across various cloud environments with responsive customer support. Logpoint focuses on on-premises deployments, providing excellent support but lacking cloud flexibility compared to Datadog.
Pricing and ROI: Datadog's pricing can be variable and costly, offering substantial ROI through operational efficiencies. Logpoint offers a fixed cost model, advantageous for budget-conscious organizations but with fewer features justifying Datadog's higher cost.
The technical support for Logpoint is very good, and I would rate it as nine out of ten.
Logpoint's customer support is not sufficient with only one engineer in the US.
It is web-based and accommodates the expansion of our organization.
Logpoint is scalable and capable of expanding.
I have received reports indicating glitches and downtimes with Logpoint.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
Dealing with foreign entities for support was a challenge, leading us to switch providers due to lack of adequate support.
Logpoint needs to be cloud-native, as currently, it is not.
The setup cost for Datadog is more than $100.
I rate the pricing at eight, suggesting it's relatively good or affordable.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
The technology itself is generally very useful.
The UEBA enables us to monitor at the device level, and SOAR provides playbooks and templates that we can modify and incorporate into the platform.
It effectively facilitates logging and log storage and assists in security event management by ingesting security events.
Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.
Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.
What are the key features of Datadog?
What benefits and ROI should users look for in reviews?
Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.
Logpoint is a cutting-edge security information and event management (SIEM) solution that is designed to be intuitive and flexible enough to be used by an array of different businesses. It is capable of expanding according to its users' needs.
Benefits of Logpoint
Some of the benefits of using Logpoint include:
Reviews from Real Users
Logpoint is a security and management solution that stands out among its competitors for a number of reasons. Two major ones are its data gathering and artificial intelligence (AI) capabilities. Logpoint enables users to not only gather the data, but also to maximize both the amount of data that can be gathered and its usefulness. It removes many of the challenges that users may face in data collection. The solution allows users to set rules for collection and then it pulls information from sources that meet the rules that have been set. This data is then broken into manageable segments and ordered. Users can then analyze these ordered segments with ease. Additionally, LogPoint utilizes both machine learning and AI technology. Users gain the ability to protect themselves from and if necessary resolve emerging threats as soon as they arise. The AI sets security parameters for a user’s system. These act as a baseline that are triggered and notify the user if anything deviates from the rules that it set up.
The chief infrastructure & security officer at a financial services firm writes, “It is a very comprehensive solution for gathering data. It has got a lot of capabilities for collecting logs from different systems. Logs are notoriously difficult to collect because they come in all formats. Logpoint has a very sophisticated mechanism for you to be able to connect to or listen to a system, get the data, and parse it. Logs come in text formats that are not easily parsed because all logs are not the same, but with Logpoint, you can define a policy for collecting the data. You can create a parser very quickly to get the logs into a structured mechanism so that you can analyze them.”
A. Secca., a Cyber Security Analyst at a transportation company, writes, “It is an AI technology because it is using machine learning technology. So far, there is nothing better out there for UEBA in terms of monitoring endpoints and user activity. It is using machine learning language, so it is right at the top. It provides that capability and monitors all of the user’s activities. It devises a baseline and monitors if there is any deviation from the baseline.”
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