Datastore Recommendation and Benchmark

❓ Choose a Datastore for GermainUX

💡 Recommendation

Elasticsearch is the recommended datastore for GermainUX, particularly for new deployments and environments that collect large volumes of monitoring, analytics, tracing, or Session Replay data.

Its distributed search and analytics architecture is well suited to:

Capability
High-volume, near-real-time ingestion
Large and evolving telemetry schemas
Fast filtering and aggregation
Full-text search
Time-based data retention
Horizontal scaling
Large dashboards and investigative queries

GermainUX also supports relational datastores when required by an organization’s existing infrastructure, operational expertise, or database standards.

📦 Supported Datastores

Datastore	Recommended use
Elasticsearch	Preferred for new deployments, large data volumes, advanced analytics, search-intensive workloads, and horizontal scalability
PostgreSQL	Suitable when an enterprise-standard relational datastore and SQL administration are preferred
MySQL	Suitable for smaller or established relational deployments
Oracle Database	Suitable for organizations standardized on Oracle infrastructure and administration
Microsoft SQL Server	Suitable for organizations standardized on Microsoft database technologies
Amazon Aurora with MySQL compatibility	May be considered for AWS-hosted relational deployments after compatibility and performance validation

Confirm the supported product version with Germain Software before deploying or upgrading.

🎯 Selection Criteria

Choose the datastore based on the complete workload rather than existing database availability alone.

Evaluate:

Criterion
Daily volume of AA Units
Peak ingestion rate
Total retained data
Raw and aggregated data-retention periods
Session Replay volume
Number and complexity of dashboards
Search and analysis workload
Concurrent GermainUX users
High-availability requirements
Backup and disaster-recovery requirements
Expected growth
Internal database expertise
Infrastructure and licensing costs
Security and compliance standards

✅ When to Choose Elasticsearch

Choose Elasticsearch when:

Condition
You are deploying GermainUX for the first time.
Monitoring volume is expected to be high.
The volume or structure of collected telemetry may grow rapidly.
Users frequently search, filter, segment, and aggregate large datasets.
Near-real-time ingestion and analysis are important.
Horizontal scalability is required.
You need efficient time-based data management.
Session Replay, tracing, or detailed real-user monitoring will produce large datasets.

Elasticsearch should normally be the starting recommendation unless your environment has a specific requirement for a relational datastore.

🗄️ When to Choose a Relational Datastore

Consider PostgreSQL, MySQL, Oracle, Microsoft SQL Server, or a compatible managed service when:

Condition
Your organization requires an approved relational database.
Your database administrators already operate the selected platform.
Monitoring volume is moderate and predictable.
Existing backup, replication, security, and disaster-recovery processes must be reused.
Licensing or operational standards favor the selected database.
Required GermainUX queries and retention can be supported at the expected scale.

Using an existing relational platform can reduce operational change, but it does not guarantee that the platform is appropriately sized for GermainUX’s ingestion and analytics workload.

⚖️ Comparison

	Elasticsearch	Relational datastore
Recommended for new GermainUX deployments	Yes	When organizational requirements favor SQL
High-volume telemetry ingestion	Strong	Depends heavily on schema, indexing, and infrastructure
Search and analytical filtering	Strong	Depends on indexes and query design
Horizontal scalability	Native distributed architecture	Product- and architecture-dependent
Time-based retention	Well suited	Requires database-specific design and maintenance
Flexible telemetry structure	Strong	More schema-dependent
Existing enterprise DBA expertise	May require Elastic expertise	Often already available
Traditional SQL access	Limited/different query model	Native
Licensing and operating costs	Deployment-dependent	Product- and license-dependent
Backup and disaster recovery	Elastic-specific procedures	Existing enterprise procedures may be reusable

🔬 Benchmark Scope

Germain Software performed internal comparative testing using:

Tested Product
Amazon Aurora with MySQL 5.7 compatibility
MySQL 5.7
Elasticsearch 7.13

The test workload included:

Workload Characteristic
Approximately 3 TB of stored data
An ingestion rate of 300–400 million AA Units per day

The benchmark was intended to compare GermainUX behavior under a high-volume workload across different datastore technologies.

These versions describe the historical benchmark configuration. They are not the current GermainUX compatibility matrix or a recommendation to deploy those exact versions.

📈 Interpreting Benchmark Results

Benchmark results should not be applied directly to another deployment because performance depends on:

Factor
CPU and memory
Disk latency, throughput, and IOPS
Node count and topology
Network performance
Index and schema design
Replication
Data distribution
Retention and cleanup activity
Query concurrency
Dashboard complexity
Session Replay volume
Backup and maintenance workload
Datastore configuration

A smaller environment can perform poorly if storage is slow or the datastore is incorrectly configured. A larger environment can perform efficiently when ingestion, retention, indexing, and infrastructure are properly designed.

📋 Validate the Selected Datastore

Before finalizing a production datastore:

Estimate daily and peak ingestion volume.
Define raw, aggregated, and Session Replay retention.
Calculate usable and physical storage requirements.
Include indexes, replicas, backups, and free-space reserves.
Reproduce representative production ingestion.
Test commonly used dashboards, searches, and analyses.
Test retention and cleanup processes.
Measure CPU, memory, disk latency, throughput, and IOPS.
Test backup and recovery.
Confirm that the architecture supports expected growth.
Validate the selected datastore and version with Germain Software.

🏁 Final Recommendation

For most new GermainUX deployments:

Use Elasticsearch unless a specific technical, operational, security, or organizational requirement justifies another supported datastore.

If your organization prefers a relational datastore, perform a representative benchmark before production deployment to confirm that it can support the expected ingestion, retention, and analytical workload.

Contact Germain Software to discuss an on-premise deployment or request assistance.

Component: Enterprise

Feature Availability: 2014.1 or later