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Description
Simplifying feature flags in Java allows for dynamic enabling and disabling of features without the need for redeployment. This system enables the implementation of various code paths through the use of predicates that are evaluated at runtime, facilitating conditional logic (if/then/else). Features can be activated not only by flag values but also through role and group access management, making it suitable for practices like Canary Releases. It supports various frameworks, starting with Spring Security, and permits the creation of custom predicates utilizing the Strategy Pattern to determine if a feature is active. Several built-in predicates are available, including white/black lists, time-based conditions, and expression evaluations. Additionally, it enables connection to external sources like a Drools rule engine for enhanced decision-making processes. To maintain clean and readable code, it encourages the use of annotations to avoid nested if statements. With Spring AOP, the target implementation is determined at runtime, influenced by the status of the features. Each execution of a feature involves the ff4j evaluating the relevant predicate, which allows for the collection of events and metrics that can be visualized in dashboards or usage trends over time. This approach not only streamlines feature management but also enhances the monitoring and analytics capabilities of your applications.
Description
Hybrid data stacks create duplication and delay: mainframe records, on prem apps, and cloud platforms often end up with mismatched copies, brittle ETL, and long lead times for “just one more feed.” Moving large datasets for every use case is slow, costly, and expands the security surface.
Rocket® Data Virtualization™ is a data virtualization and federated query solution that enables a governed, virtual data model across mainframe, distributed, and cloud sources—so BI tools, analysts, and applications can query sensitive data in place.
Key capabilities:
• Federated SQL queries/joins across heterogeneous sources with pushdown
• Standard connectivity (e.g., JDBC/ODBC/REST) for BI, analytics, and apps
• Virtual views/semantic layer to simplify access and reuse logic
• Centralized security controls, auditing, and masking (where supported)
• Optional caching/materialization to balance performance and freshness
Result: faster time to data with less ETL and lower migration risk.
API Access
Has API
API Access
Has API
Integrations
Amazon DynamoDB
Apache HBase
ArangoDB
Couchbase
Docker
Drools
Eureka ERP
HashiCorp Consul
Hazelcast
IBM Cloud
Integrations
Amazon DynamoDB
Apache HBase
ArangoDB
Couchbase
Docker
Drools
Eureka ERP
HashiCorp Consul
Hazelcast
IBM Cloud
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
FF4J
Website
ff4j.org
Vendor Details
Company Name
Rocket Software
Founded
1990
Country
United States
Website
www.rocketsoftware.com/product-categories/data-virtualization
Product Features
Feature Management
A/B Testing
Entitlement Management
Feature Alerts
Feature Flag / Toggle
Feature Rollout Management
KPI Monitoring
Kill Switch
Multivariate Testing
Product Experimentation
Whitelist Creation