Splunk Enterprise Security and Elastic Search are competitors in the data management and analysis space. Splunk has the upper hand in comprehensive feature offerings like operational intelligence and integrations, while Elastic Search shines with its open-source availability and scalability.
Features: Splunk Enterprise Security offers rapid search capabilities for enhanced response times, integration with diverse data sources, and compliance support. Elastic Search is appreciated for its open-source nature, fast search speeds, and enhanced visualization via Kibana.
Room for Improvement: Splunk could refine its operational workflow and GUI for better usability, while Elastic Search could simplify its initial setup and improve documentation.
Ease of Deployment and Customer Service: Splunk provides flexible deployment options and responsive customer service. Elastic Search is easy to deploy and benefits from strong community support, though guidance for large-scale setups could improve.
Pricing and ROI: Splunk is high-cost, but users find value in its robust features. Elastic Search offers a low-cost entry with scaling flexibility, though premium features can be expensive. Both offer significant ROI, with Splunk justifying its cost through comprehensive capabilities and Elastic Search through cost-effectiveness in smaller settings.
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.
I would rate technical support from Elastic Search as three out of ten.
The customer support for Elastic Search is quite good.
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.
I can actually add more storage and memory because I host it in the cloud.
I would rate the scalability of Elasticsearch as an eight.
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.
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.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
The stability of Elasticsearch was very high.
Elastic Search is quite stable.
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.
It provides a stable environment but needs to integrate with ITSM platforms to achieve better visibility.
This can create problems for new developers because they have to quickly switch to another version.
It is primarily based on Unix or Linux-based operating systems and cannot be easily configured in Windows systems.
The consistency and stability of Elasticsearch are commendable, and they should keep up the good work.
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.
We used the open-source version of Elasticsearch, which was free.
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 | 20.4% |
Lucidworks | 11.6% |
Coveo | 8.6% |
Other | 59.4% |
Product | Market Share (%) |
---|---|
Splunk Enterprise Security | 9.2% |
Wazuh | 10.2% |
IBM Security QRadar | 7.0% |
Other | 73.6% |
Company Size | Count |
---|---|
Small Business | 32 |
Midsize Enterprise | 8 |
Large Enterprise | 36 |
Company Size | Count |
---|---|
Small Business | 109 |
Midsize Enterprise | 49 |
Large Enterprise | 257 |
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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