As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HANA, or high-throughput SQL Server clusters, EHR systems, and real-time big data analytics, memory-bound databases often force enterprises to over-provision compute cores (vCPUs) to get the RAM capacity and storage bandwidth they need, driving up costly third-party software licensing fees.
Today, we are thrilled to announce the general availability of the M4N machine series in Google Compute Engine, purpose-built for I/O intensive, high-memory workloads, the second offering in our network- and block-storage optimized VM family. Compared to similar offerings from other hyperscalers M4N provides the highest per-core IOPS and throughput for high-memory instances, and over 20% TCO reduction for Oracle databases. M4N is also the industry’s first instance of network and block storage optimized with higher memory ratios (up to 26:1) and size (6TB).
Powered by 5th Gen Intel® Xeon® Scalable processors and built on Google Cloud's custom Titanium offload architecture, M4N instances deliver up to 25,000 MiB/s (25 GiB/s) of aggregate host storage performance and up to 1 million IOPS when paired with Hyperdisk Extreme — doubling the block storage performance of current M4 instances. M4N targets workloads that demand both extreme high-density RAM and uncompromising I/O performance, complementing our existing memory-optimized families (such as M1, M2, M3, M4, and X4) by solving specific storage and network bottlenecks for high-throughput enterprise applications.
Oracle, SAP HANA, SQL Server, IBM DB2, MySQL, PostgreSQL Memory-to-core ratios (up to 26. 57 GB/vCPU) paired with 25 GiB/s storage for rapid data ingestion, transaction logging, and zero-stall backup cycles. Milvus, Pinecone, Qdrant, Vespa, Redis, In-Memory Context Caching Sub-millisecond similarity search across massive vector indexes in RAM, combined with 400 Gbps network bandwidth for distributed model retrieval. Epic Systems (Operational Database), SAP ECC, SAP S/4HANA Sustained I/O headroom that prevents query latency spikes during peak clinical/transactional hours.