Splunk Enterprise Security and Elastic Observability both compete in the realm of data analytics and security information management. Splunk appears to have an edge with its comprehensive search capabilities and advanced features despite its higher cost.
Features: Splunk Enterprise Security provides robust data ingestion, fast and comprehensive search capabilities, and a powerful schema-on-read system that allows for a broad range of data handling and analysis. It utilizes Search Processing Language (SPL) to enhance these operations. Elastic Observability is known for its powerful search analytics and seamless integration that provide great flexibility, although it does not offer some of the advanced features present in Splunk.
Room for Improvement: Splunk could improve its user interface and simplify the operational workflow and setup. Performance and visualization stability also require attention. Elastic Observability could enhance visualization and application performance monitoring (APM) features, and increase automation to improve the user interface.
Ease of Deployment and Customer Service: Splunk supports a range of deployment options including on-premises, public, hybrid, and private clouds, with access to a large support network, though response times and quality can vary. Elastic Observability offers similar deployment flexibility with an emphasis on affordability and community-based support, though some users recommend enhanced technical support services.
Pricing and ROI: Splunk's pricing, based on data volume, can lead to unpredictable costs, but it offers significant value to enterprises needing extensive capabilities. Elastic Observability is more cost-effective with clear licensing terms, making it appealing to smaller organizations. Both solutions can deliver good ROI, but Elastic's lower cost entry is particularly attractive for budget-conscious users.
I have noticed a return on investment with Splunk Enterprise Security, as it delivers substantial value for money.
Customers see the value in investing in this solution, particularly when it helps resolve issues quickly, turning a potential 20-hour response into one hour.
Splunk's cost is justified for large environments with extensive assets.
If you want to write your own correlation rules, it is very difficult to do, and you need Splunk's support to write new correlation rules for the SIEM tool.
They try to close issues as soon as possible, often just offering documentation links.
They are responsive and effectively resolve issues.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
They struggle a bit with pure virtual environments, but in terms of how much they can handle, it is pretty good.
It is easy to scale.
It's big in a Central European context, and small from a Splunk North American context.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
They test it very thoroughly before release, and our customers have Splunk running for months without issues.
It provides a stable environment but needs to integrate with ITSM platforms to achieve better visibility.
It is very stable.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
One example is the inability to monitor very old databases with the newest version.
Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal.
Improving the infrastructure behind Splunk Enterprise Security is vital—enhanced cores, CPUs, and memory should be prioritized to support better processing power.
Splunk Enterprise Security is not something that automatically picks things; you have to set up use cases, update data models, and link the right use cases to the right data models for those detections to happen.
What Splunk could do better is to create an API to the standard SIEM tools, such as Microsoft Sentinel.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
I saw clients spend two million dollars a year just feeding data into the Splunk solution.
The platform requires significant financial investment and resources, making it expensive despite its comprehensive features.
Splunk is priced higher than other solutions.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
This capability is useful for performance monitoring and issue identification.
I assess Splunk Enterprise Security's insider threat detection capabilities for helping to find unknown threats and anomalous user behavior as great.
They have approximately 50,000 predefined correlation rules.
Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.
Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.
What are Elastic Observability's key features?Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.
Splunk Enterprise Security is widely used for security operations, including threat detection, incident response, and log monitoring. It centralizes log management, offers security analytics, and ensures compliance, enhancing the overall security posture of organizations.
Companies leverage Splunk Enterprise Security to monitor endpoints, networks, and users, detecting anomalies, brute force attacks, and unauthorized access. They use it for fraud detection, machine learning, and real-time alerts within their SOCs. The platform enhances visibility and correlates data from multiple sources to identify security threats efficiently. Key features include comprehensive dashboards, excellent reporting capabilities, robust log aggregation, and flexible data ingestion. Users appreciate its SIEM capabilities, threat intelligence, risk-based alerting, and correlation searches. Highly scalable and stable, it suits multi-cloud environments, reducing alert volumes and speeding up investigations.
What are the key features?Splunk Enterprise Security is implemented across industries like finance, healthcare, and retail. Financial institutions use it for fraud detection and compliance, while healthcare organizations leverage its capabilities to safeguard patient data. Retailers deploy it to protect customer information and ensure secure transactions.
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