

Splunk Enterprise Security and Elastic Search compete in the security and log management space. Splunk appears to have the upper hand due to its comprehensive features and strong support network, despite its higher cost and complexity.
Features: Splunk Enterprise Security offers advanced security operations capabilities, including threat detection, risk-based alerting, and seamless data integration with customizable dashboards. It is ideal for managing diverse data sources. Elastic Search is known for its scalability, fast search capabilities, and strong log monitoring with analytics through Kibana, and its open-source nature allows extensive customization.
Room for Improvement: Splunk's high cost, complex architecture, and steep learning curve are notable challenges. Users express the need for better integration and enhanced machine learning features. Elastic Search could improve ease of use during setup and integration, particularly in visualization and AI capabilities, with better documentation and more out-of-the-box functionalities.
Ease of Deployment and Customer Service: Splunk offers deployment options across public, private, and hybrid environments and benefits from a robust support network, although user experiences with response times vary. Elastic Search's open-source model facilitates easier cloud deployment, backed by strong community support, though it requires significant technical expertise and lacks direct support compared to Splunk.
Pricing and ROI: Splunk's high data ingestion costs may be prohibitive for smaller organizations, yet its comprehensive features offer substantial ROI for larger enterprises. Elastic Search is cost-effective due to its open-source availability, though support and expertise may incur additional expenses. Its node-based pricing provides flexibility and favorable ROI for businesses with the necessary technical expertise.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
The documentation for Splunk Enterprise Security is outstanding. It is well-organized and easy to access.
We couldn't calculate what would have been the cost if they had actually gotten compromised; however, they were in the process, so every investment was returned immediately.
On average, my SecOps team takes probably at least a quarter of the time, if not more, to remediate security incidents with Splunk Enterprise Security compared to our previous solution.
The customer support for Elastic Search is one of the best I have ever tried.
They have always been really responsible and responsive to my requests.
It has been sufficient to visit conferences such as SCALE in Southern California Linux Expo, where Elastic Search has a booth to talk to their staff.
We have paid for Splunk support, and we’re not on the free tier hoping for assistance; we are a significant customer and invest a lot in this service.
I have had nothing but good experiences with Splunk support, receiving timely and helpful replies.
We've had great customer success managers who have helped us navigate scaling from 600 gigs to 30 terabytes.
I would rate its scalability a ten.
Since we're on the cloud, whenever we need to upgrade or add resources, they handle everything.
We haven't encountered any problems so far, and there is the potential for auto-scaling.
We currently rely on disaster recovery and backup recovery, which takes time to recover, during which you're basically blind, so I'm pushing my leadership team to switch over to a clustering environment for constant availability.
It is one of the things that separates it from other tooling, and if not, it is the most scalable solution out there.
They struggle a bit with pure virtual environments, but in terms of how much they can handle, it is pretty good.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
The stability of Elasticsearch was very high.
When you put one keyword, everything related to that keyword in your ecosystem will showcase all the results.
They test it very thoroughly before release, and our customers have Splunk running for months without issues.
Splunk has been very reliable and very consistent.
We need more SMEs, and there is no mechanism to tell us about indexer or search head issues.
From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs.
If I need to parse one million records saved into Elastic Search, it becomes a nightmare because I need to do the pagination, and it is very problematic in that regard.
Observability features like search latency, indexing rate, and maybe rejected requests should be added to make the platform more reliable and accessible for everyone.
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.
For any future enhancements or features, such as MLTK and SOAR platform integration, we need more visibility, training, and certification for the skilled professionals who are working.
On the AWS side, it is very expensive because they charge based on query basis or how much data is transferred in and out, making it very expensive.
Having the hosted solution and not having to pay for essentially a DevOps person on staff to manage makes it affordable.
You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
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.
I find it to be affordable, which is why every industry uses it.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis.
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.
Splunk Enterprise Security provides the foundation for unified threat detection, investigation, and response, enabling fast identification of critical issues.
| Product | Market Share (%) |
|---|---|
| Elastic Search | 13.6% |
| Lucidworks | 7.5% |
| OpenText Knowledge Discovery (IDOL) | 6.7% |
| Other | 72.2% |
| Product | Market Share (%) |
|---|---|
| Splunk Enterprise Security | 7.4% |
| Wazuh | 7.3% |
| IBM Security QRadar | 5.6% |
| Other | 79.7% |

| Company Size | Count |
|---|---|
| Small Business | 37 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 109 |
| Midsize Enterprise | 50 |
| Large Enterprise | 264 |
Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.
Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.
Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.
At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.
Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.
In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.
Splunk Enterprise Security delivers powerful log management, rapid searches, and intuitive dashboards, enhancing real-time analytics and security measures. Its advanced machine learning and wide system compatibility streamline threat detection and incident response across diverse IT environments.
Splunk Enterprise Security stands out in security operations with robust features like comprehensive threat intelligence and seamless data integration. Its real-time analytics and customizable queries enable proactive threat analysis and efficient incident response. Integration with multiple third-party feeds allows detailed threat correlation and streamlined data visualization. Users find the intuitive UI and broad compatibility support efficient threat detection while reducing false positives. Despite its strengths, areas such as visualization capabilities and integration processes with cloud environments need enhancement. Users face a high learning curve, and improvements in automation, AI, documentation, and training are desired to maximize its potential.
What Are the Key Features of Splunk Enterprise Security?In specific industries like finance and healthcare, Splunk Enterprise Security is instrumental for log aggregation, SIEM functionalities, and compliance monitoring. Companies leverage its capabilities for proactive threat analysis and response, ensuring comprehensive security monitoring and integration with various tools for heightened operational intelligence.
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