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Download IgniteARCHITECTURAL BACKBONE
CORE FEATURES
DATA PLACEMENT & PROCESSING
OPERATIONAL EXCELLENCE
ADDITIONAL USE CASES
Download IgniteARCHITECTURAL BACKBONE
CORE FEATURES
DATA PLACEMENT & PROCESSING
OPERATIONAL EXCELLENCE
ADDITIONAL USE CASES
Operational Analytics
Transactional OR Analytical? Choose Both.
Concurrent queries on live transactional data without blocking writes
Concurrent queries on live transactional data without blocking writes
Stale Dashboards, Blocked Transactions
Business decisions wait for data. Run analytics on the production database and transactions queue behind table locks. Replicate to a warehouse and dashboards show yesterday's numbers. The operations team watches real-time metrics lag behind actual system state.
ETL pipelines add hours of latency between events and insights. Analytical queries on transactional systems create contention that degrades application performance. Maintaining separate OLTP and OLAP infrastructure doubles operational overhead while data freshness suffers.
How Apache Ignite Solves This
Apache Ignite provides lock-free analytical queries on live transactional data through snapshot isolation
Lock-Free Queries
Snapshot isolation enables analytical queries to read consistent data snapshots without blocking concurrent writes. Queries run on committed data without acquiring read locks. Transactions continue writing while analytical queries execute concurrently. Eliminates the need for table-level locks during aggregation operations.
Single Platform
Memory-first architecture delivers low-latency access for both transactional writes and analytical reads. Standard SQL aggregations (SUM, COUNT, AVG, GROUP BY) run directly on transactional data. No ETL pipelines or separate OLAP infrastructure. Eliminates data replication latency and synchronization complexity.
Architecture Pattern
Concurrent Analytical Queries On Transactional Data
Applications execute transactional writes while analytical queries run concurrently on consistent snapshots without blocking operations.
Integration Pattern: Transactional applications write to Apache Ignite tables using standard ACID operations. Analytical queries use SQL aggregations (SUM, COUNT, GROUP BY, HAVING) to generate reports and dashboards directly from transactional tables.
Consistency Model: Snapshot isolation ensures analytical queries read consistent data at point-in-time without blocking writes. Queries see committed transactions only. No table locks or read blocking during aggregations.
Performance Characteristics: Memory-first storage delivers low-latency analytical query execution. Concurrent writes continue without degradation during query execution. Horizontal scalability handles both transactional and analytical workload growth.
When This Pattern Works
This architecture pattern is best for:
- Operational reporting requiring real-time transactional data
- Compliance dashboards with audit trail queries
- Business intelligence on live operational data
- Systems where ETL latency creates business risk
Example Use Cases:
- Financial Reporting: Real-time account balances and transaction summaries without blocking payment processing
- Inventory Management: Current stock levels and movement analysis without blocking order fulfillment
- Operational Dashboards: Live metrics and KPIs calculated directly from transactional data
Key Benefits
Zero Lock Contention
Snapshot isolation enables analytical queries without acquiring read locks. Transactional writes proceed without blocking during query execution. Queries read consistent snapshots at point-in-time. Eliminates table-level locks required by traditional databases during aggregations.
Eliminate ETL Complexity
Single platform supports both transactional and analytical workloads. No data replication to separate OLAP systems. Analytical queries access current data without ETL latency. Reduces infrastructure complexity and operational overhead.
Standard SQL Aggregations
Support for common SQL aggregations (SUM, COUNT, AVG, MIN, MAX, GROUP BY, HAVING). Familiar query syntax for reporting and business intelligence. SQL-based analytics without learning specialized query languages. Standard JDBC/ODBC connectivity for BI tools.
Real-Time Insights
Analytical queries operate on live transactional data without replication delays. Memory-first architecture delivers low-latency query execution. Operational dashboards reflect current state immediately. Business decisions based on real-time data.
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Use Cases Overview