Splunk Enterprise Security and Elastic Search compete in the data analytics category, each excelling in specific areas that cater to different organizational needs. Splunk Enterprise Security seems to have the upper hand due to its comprehensive feature set and strong focus on incident response and operational intelligence.
Features: Splunk Enterprise Security offers rapid search capabilities, extracts data from multiple sources, and provides advanced analytics tools, which are crucial for incident response and operational intelligence. It also includes predefined user cases and allows for flexible dashboard creation. Elastic Search is recognized for its strong indexing capabilities, scalability, and supports fast search engines which are ideal for managing large data volumes. It integrates effortlessly with multiple platforms and supports multilingual environments.
Room for Improvement: Splunk Enterprise Security could update its GUI, simplify deployment, and improve integration with third-party tools. It also faces criticism for its complex licensing model. Elastic Search needs to enhance its user interface for easier use, improve alerting features, and streamline integration efforts with other security tools to ease deployment for new users.
Ease of Deployment and Customer Service: Splunk Enterprise Security is flexible, working both on-premises and in the cloud with generally good technical support, though responsiveness can vary. Elastic Search, typically on-premises, offers robust performance with strong community support, although vendor support might require premium services for increased responsiveness.
Pricing and ROI: Splunk Enterprise Security's pricing is considered high, being volume-based, which can be prohibitive for smaller enterprises, but its feature set often justifies the cost for larger ones. Elastic Search is generally more cost-effective, offering a flexible, open-source licensing model and the option to pay for premium features only if necessary, providing scalability for organizations managing and customizing it internally.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
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.
The technical support for Splunk met my expectations.
I can actually add more storage and memory because I host it in the cloud.
They struggle a bit with pure virtual environments, but in terms of how much they can handle, it is pretty good.
It provides a stable environment but needs to integrate with ITSM platforms to achieve better visibility.
It is very stable.
This can create problems for new developers because they have to quickly switch to another version.
What Splunk could do better is to create an API to the standard SIEM tools, such as Microsoft Sentinel.
Splunk Enterprise Security would benefit from a more robust rule engine to reduce false positives.
Splunk could enhance its offerings by incorporating modules for network detection and response and fraud management.
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.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
Aggregation is faster than querying directly from a database, like Postgres or Vertica.
Splunk Enterprise Security's most valuable features are its stability and the robust Splunk Search Processing Language.
The Splunk Enterprise Security's threat-hunting capabilities have been particularly useful in later releases.
They have approximately 50,000 predefined correlation rules.
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 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.
We monitor all Indexing and Search reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.