![]() Splunk customers have to determine what data goes into Splunk, and what “falls on the floor.” This approach risks losing visibility into potentially important events. (Because how can you decide today what might be important years from now? You don't need to determine what's relevant until you need it. Splunk Cloud also doesn’t doesn’t allow real-time queries by default - you would need a support ticket for that.Įlastic enables you to collect all data at ingest and retain it, via data transforms and ingest pipelines. This time can have serious consequences when you’re facing issues that impact your customers and revenue. Data in Splunk's frozen tier must be restored before searching, and users may have to wait up to 24 hours for the data to be searchable. With Splunk, accessing historical data is slow. Elastic search, analytics, and machine learning run efficiently on all data tiers. Data tiering is available for all observability data, providing greater flexibility in how you store, search, and analyze. Manage your business, not your dataįaster, smarter data access and retention The answers you need, in millisecondsĮlastic’s real-time search queries take milliseconds, not seconds, and historical queries take minutes, not hours. Splunk requires you to use specialized languages like SPL for visualizations and dashboards. This flexibility allows any user to quickly pivot data and share across teams, enabling real-time collaboration, from anywhere. You don’t need to be a data scientist to create and run an ML job or a query. The Splunk ML toolkit, on the other hand, is an add-on application that may come with additional work for your team, including the need to code models in SPL.ĭemocratized machine learning and analyticsĮlastic Observability provides intuitive drag-and-drop capabilities and wizard-based workflows to analyze and visualize all your data and uncover trends. Plus, out-of-the-box capabilities such as log categorization and APM correlations quickly help root cause analysis, reducing costly outages. As a result, you’ll be better able to catch issues before they happen. Machine learning that’s not an add-onįlexible and customizable machine learning (ML) is natively built into the Elastic platform and can be applied on any type of data, whether operational (metrics, logs, traces) or business data. Splunk customers, on the other hand, would need to purchase as many as seven separate products (multiple Splunk observability products, Splunk Cloud, and Splunk Enterprise) to achieve full observability functionality, which would result in silos. This means you can eliminate data silos and gain full-scale visibility across all your environments from one place, without add-on products or pricing. Simple, smart, integrated experience for Observability Logs, metrics, and traces in one platformĮlastic Observability is a full-suite solution that delivers integrated log analytics, application performance monitoring (APM), metrics, and traces in a single, fully unified platform. ![]() Modern application and operations teams are finding freedom, flexibility, and accelerated productivity with Elastic Observability. Many companies have adopted Splunk Enterprise and have a choice to make, since Splunk offers fragmented observability with Splunk Enterprise, Splunk Cloud, and Splunk Observability with different pricing models.Įlastic offers a fast, simple, solution that positions companies for the future. As a result, teams need smarter analytics, access, and retention across all their data - instantly and from anywhere - in order to resolve issues, make decisions, and ensure resiliency. Businesses everywhere are facing a challenging environment: increased cost pressures coupled with high volumes of data generated by complex, distributed, cloud-native environments. ![]()
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