Splunk to Elastic Migration

Elasticsearch is a distributed search and analytics engine that forms the core of the Elastic Stack — a suite of products that also includes Logstash (data ingestion and transformation), Kibana (visualization and dashboards), and Beats (lightweight data shippers). Together, the Elastic Stack is widely used for log management, full-text search, security analytics, and observability across enterprise environments.

Elasticsearch stores and indexes data as JSON documents and uses a powerful query language (Elasticsearch Query DSL and KQL) for fast search and aggregation across large data volumes. Organizations migrating from Splunk to Elastic do so to bring their observability and security data onto the Elastic Stack. Crest Data manages the full migration — automating the conversion of Splunk dashboards, SPL queries, and alerts into their Kibana and Elasticsearch equivalents.

Elasticsearch’s source code is publicly available under the Elastic License 2.0 (ELv2), which permits free use, modification, and self-hosting for most purposes. A fully open-source fork called OpenSearch, maintained by AWS under the Apache 2.0 license, is also available for organizations requiring an OSI-certified open-source licence.

Elastic offers a free self-managed tier with core features, as well as paid subscription tiers (Standard, Gold, Platinum, Enterprise) that unlock advanced security, machine learning, and enterprise support capabilities. Elastic Cloud is available as a managed SaaS offering with flexible pricing. Crest Data will help you determine the appropriate Elastic licensing tier for your requirements as part of the migration scoping process.

Elasticsearch is best described as a search and analytics engine rather than a traditional relational database. It stores data as indexed JSON documents optimised for fast full-text search, aggregation queries, and log analysis — making it highly performant for the kinds of operational and security data that organizations typically manage in Splunk.

While Elasticsearch is not designed for transactional workloads or relational data models, it is exceptionally well-suited to the log management, event analytics, and security monitoring use cases that form the core of most Splunk deployments. When migrating from Splunk to Elastic, Crest Data ensures your data is correctly structured and indexed in Elasticsearch for optimal query performance and dashboard rendering in Kibana.

Splunk’s SPL (Search Processing Language) and Elasticsearch’s query languages (KQL and Elasticsearch Query DSL) serve the same fundamental purpose — searching and aggregating data — but use different syntax and data models.

Common SPL patterns have direct equivalents in Kibana Query Language. Aggregations performed with SPL’s stats command are handled through Kibana Lens visualizations or Elasticsearch aggregation APIs. More complex SPL involving lookups, subsearches, and multi-step pipelines require careful translation.

Crest Data’s migration engine automates the bulk of this SPL-to-KQL translation, processing your entire library of saved searches and dashboard queries in one pass. A validation report highlights any queries flagged for manual review, which are handled by our certified Elastic engineers. The result is a complete Kibana dashboard library that reproduces your existing Splunk monitoring coverage.

The ELK Stack is the combination of Elasticsearch (data storage and search), Logstash (data ingestion and transformation pipeline), and Kibana (visualization and dashboards). When Beats — lightweight data shippers for logs, metrics, and other telemetry — are added, the stack is commonly referred to as the Elastic Stack.

The Elastic Stack is a comprehensive platform for log management, security analytics, and operational intelligence — covering many of the same use cases as Splunk. Organizations that choose to migrate from Splunk to Elastic gain access to a flexible, well-supported platform with a large ecosystem of integrations and an active open-source community. Crest Data’s migration service handles the complete transition from Splunk to Elastic — including data pipeline reconfiguration, dashboard migration, and production validation — so your team can focus on operations rather than the mechanics of migration.