We’re excited to introduce GridGain 9.1 with powerful new capabilities for hybrid transactional and analytical processing. These features enable teams to run real-time analytics on live operational data – without impacting transactional performance.
Traditionally, organizations had to choose between systems optimized for transactions (OLTP) and those tuned for analytics (OLAP). Maintaining separate data stacks often meant dealing with fragile pipelines and delayed insights. Trying to converge both workloads on a single data store, such as a traditional RDBMS, usually led to degraded performance for both OLTP and OLAP.
GridGain 9.1 eliminates this trade-off by enabling both workloads to run efficiently on the same platform. With GridGain 9.1, you can:
- Ingest and process operational data in real time
- Run fast, complex analytical queries on fresh data
- Avoid ETL pipelines, batch syncs, and separate analytics stores
GridGain 9.1 delivers the best of both worlds – low-latency transactions and high-performance analytics – within a unified platform.
Key Capabilities of GridGain 9.1
GridGain 9.1’s new capabilities are built around an enhanced columnar storage engine that is natively integrated into the platform. They include:
1. Secondary Storage
The core enabler of GridGain 9.1 is the concept of secondary storage. This allows selected tables to use two storage formats simultaneously: primary storage optimized for OLTP and secondary storage optimized for OLAP. The secondary storage layer asynchronously ingests updates from the transactional store, providing up-to-date analytics without interfering with transaction performance.
This ensures there are no dual writes or ETL pipelines, and makes data available for analytics with sub-second latency while guaranteeing full transactional consistency with no dirty reads.
This architecture makes real-time analytics possible without compromising transactional throughput.
2. Columnar Storage Engine
GridGain 9.1 introduces an enhanced columnar format for secondary storage that is highly efficient for analytical workloads involving scans, filtering, and aggregations. This engine complements GridGain’s traditional row-based Page Memory storage, optimized for transactional workloads. Together, they enable seamless OLTP and OLAP on the same data, with the complexities hidden from the user.
3. Unified SQL Engine
GridGain’s SQL engine is fully aware of both the secondary storage layer and the dual storage formats. Users write standard SQL queries; the query planner automatically routes them to the optimal engine – row or columnar – based on the workload.
In this architecture, transactional queries continue using the row store. Analytical queries are directed to the columnar store and benefit from projection pushdown, vectorized execution, and other optimizations.
The engine also supports cross-format queries, allowing joins across traditional and HTAP-enabled tables. This offers powerful performance and flexibility without requiring changes to application logic.
The Secret Sauce: Workload Isolation
A columnar store engine alone is not enough. The real power of GridGain 9.1 lies in workload isolation – the ability to prevent analytical workloads from disrupting transactional operations.
OLTP systems often have strict performance requirements with tightly tuned resources. In contrast, OLAP workloads can be sporadic, bursty, and resource-intensive. Without proper isolation, analytics can become a “noisy neighbor” and degrade the performance of mission-critical OLTP operations.
GridGain 9.1 addresses this with several safeguards:
- Asynchronous ingestion: Data is streamed from the row store to the columnar store in the background, ensuring that transactions never wait – even if the columnar layer is under load.
- Lock-free queries: Analytical queries are lock-free, avoiding contention with transactional operations.
- Optional workload segregation: You can place columnar storage on separate nodes to fully isolate compute and memory resources.
- Memory quotas: Per-query and per-node SQL memory quotas prevent analytical workloads from consuming excessive resources.
Together, these mechanisms ensure OLTP remains fast and predictable – even as you introduce rich analytics.
Why This Matters
With GridGain 9.1, developers and architects can power real-time dashboards and analytics directly on operational data, and eliminate delays between data ingestion and insight. GridGain 9.1 simplifies the data stack by unifying OLTP and OLAP on one platform, and reduces total cost of ownership by avoiding separate OLAP systems and ETL pipelines.
Common use cases include fraud detection, recommendation engines, IoT telemetry analysis, and user behavior monitoring – any scenario where timely insights from fresh data are critical.
Getting Started
To try GridGain 9.1:
- Download and install GridGain 9.1
- Follow the Getting Started Guide to enable the columnar-based secondary storage on your tables