Dynatrace vs. Coralogix: application investigations and long-term logs

An established Java application already has OneAgent monitoring, service relationships, and useful slow-request views. The new requirement comes from elsewhere: keep six months of audit logs for occasional business and security investigations without treating every record as frequently searched data.

Dynatrace versus Coralogix is often about dividing those responsibilities. Keeping a platform that already explains critical requests may save substantial work. When logs become the dominant workload and access frequency varies widely, Coralogix's processing and storage routing deserve closer attention.

Guance Editorial Team · Reviewed October 21, 2026. This guide compares Dynatrace SaaS/Grail with Coralogix cloud analysis. It does not assume Dynatrace Managed has every current SaaS capability. No performance or cost benchmark was performed.

A topology does not explain every business event

Suppose the payment service is waiting for a database connection. OneAgent's request and process context can help locate the problem. On supported technologies, Full-Stack Monitoring also provides code-level visibility, CPU and memory profiling, and process monitoring. Coverage depends on the platform, runtime, Agent version, and monitoring mode; automatic discovery is not universal configuration-free coverage. Support matrix, Full-Stack scope

Explaining repeated attempts caused by a business rule may still require application logs. Dynatrace processes ingested logs through OpenPipeline and stores them in Grail for analysis through Logs, Notebooks, dashboards, and DQL. Shared request and resource context depends on collected data and fields; a topology cannot manufacture missing evidence. Log Analytics

Coralogix also accepts traces and provides related-data navigation from spans. The chosen log datasets determine whether the query uses Frequent Search or archives. Existing OTel collection can remain useful, but information previously obtained through OneAgent's deeper process monitoring needs its own replacement assessment. Span-related data

Displaying a trace in both platforms is therefore only the beginning. The important question is whether the evidence that explained connection-pool waits, retries, and dependency failures remains available.

Six months of logs and the last ten minutes have different jobs

Coralogix performs some monitoring while data is arriving, then uses TCO priorities to organize storage and access. High, or Frequent Search, uses OpenSearch hot storage. Medium, or Monitoring, and Low, or Compliance, keep raw data in customer storage while remaining queryable through DataPrime. The platform is neither entirely index-free nor priced identically for every log. TCO Optimizer

Payment errors requiring frequent interactive investigation may belong in High. Records used for ongoing monitoring but less frequent individual searches may fit Monitoring. Occasional historical evidence may fit Compliance. Each change also affects available workflows: custom dashboards can include Monitoring data, but not Compliance data in the same way. Dashboard support

Dynatrace has different ways to organize Grail log consumption. DPS supports separately metered Retain and Query, as well as Retain with Included Queries, which includes queries for the configured time range. Queries covering data outside that included range follow the applicable separate consumption rules. Included usage still has a volume boundary: the aggregate scan allowance over 24 hours is fifteen times the log volume retained in that window. Dynatrace says its team will help evaluate and optimize consumption if that allowance is exceeded; it is not an unlimited-scanning promise. Saying every Dynatrace query always adds an individual query charge is therefore too broad. DPS log models

Repeated investigations over recent hours and an occasional lookup six months later need different access patterns. One universal retention and query policy may simultaneously underserve incident responders and overprovision historical data.

An archive still has operating limits

A configured Coralogix S3 archive stores logs and traces as Parquet. Region and permissions must match the service configuration. Long retention still involves capacity, requests, lifecycle policies, encryption, and access management. A customer-owned bucket is neither free storage nor a customer-operated copy of the Coralogix backend. Archive configuration

Being able to query archives without first restoring the entire history to a hot index is useful. Scanning and result limits still apply. A six-month search without a service constraint is a different workload from a lookup with a date and business identifier. Archive query limits

Keeping files also does not ensure that the later investigation will succeed. A field removed before storage cannot be recovered, and a reviewer may lack access. For audit evidence, deletion rights, uninterrupted delivery, and verifiable retention matter more than the name of a Compliance tier.

Dynatrace included queries also need a time boundary. If a bucket retains thirty days but only a recent interval has Included Queries, a query extending beyond that interval can incur consumption for older data. Daily recent-log searches and a month-end aggregate can therefore have different billing behavior. Neither “all historical queries are free” nor “the configuration failed because an old query cost money” is an appropriate inference.

Historical incidents can span several processing and access-policy changes. Keep the conditions under which records entered the system available to investigators; the current configuration alone is not a complete explanation of historical query results.

Equal host counts need not mean equal consumption

Host-based Dynatrace DPS Full-Stack Monitoring uses memory GiB-hours. Physical or virtual host RAM is rounded up in 0.25 GiB increments with a 4 GiB minimum, and monitoring is measured in 15-minute intervals. Application-only container monitoring has its own scope and rules. This is more specific than hosts multiplied by hours. Full-Stack consumption

For ten 32 GiB VMs monitored all day under those simplified assumptions:

10 × 32 GiB × 24 hours = 7,680 GiB-hours/day

That is usage, not a dollar quote. The rate card supplies the applicable price; logs, extended trace ingestion, and other capabilities need their own accounting. Included allowances should not be charged twice, but the presence of OneAgent does not mean every data product is included.

Coralogix consumption depends on entity type and pipeline priority. Its current documentation lists 0.75, 0.32, and 0.12 units per GB of High, Medium, and Low logs. Blocked logs still incur processing consumption. A six-month retention estimate must include the relevant customer storage and contract, not just an ingestion ratio. Usage measurement

Splitting the platforms creates another handoff

Keeping Dynatrace for application investigation while sending selected logs to Coralogix is a viable arrangement. The handoff must carry the correct time, service, environment, and request identifier. Independent successful searches in both products do not prove that engineers can move between them effectively.

Routing can add transmission costs and duplicate consumption. Parsing rules may diverge: a link still opens after one platform changes a field name, but its query finds nothing. Maintaining that connection is ongoing work rather than a one-time integration task.

Dynatrace itself supports OTel and allows service-by-service combinations with OneAgent. It is not a proprietary-only input path. Preserve the distinction between information supplied by OneAgent, external OTel data, and the queries that use them; a migration cannot be reduced to changing an endpoint. Dynatrace and OTel

When to keep the existing system

If critical applications depend on Dynatrace's process, code, and resource evidence, and Grail can serve the log workload, refining the current configuration is often the simpler choice. Different query and retention settings may be enough for the new requirement.

Coralogix becomes attractive when logs dominate both work and spending, access patterns differ markedly, and the team can maintain routing and customer storage. The gain depends on useful investigations surviving the tier changes—not on a guaranteed multiple of cost savings.

A split deployment can preserve useful assets, provided responsibility for evidence and cross-platform navigation is explicit. It makes sense only when that continuing work is preferable to rebuilding the whole monitoring environment.

Connecting logs and traces in Guance

Guance's log details provide field inspection and related-data navigation. Bring in relevant application, host, and trace data to see whether a familiar incident can be investigated without repeated handoffs.

Collection quality, fields, and retention remain prerequisites. A SaaS backend can reduce some operating work, while data conventions and original records still need owners. Include service costs and duplicate delivery alongside the existing platform.