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MASTERING SINGLESTORE DATABASE: DISTRIBUTED SQL AT SCALE: Deploy, optimize, and scale hybrid transactional/analytical workloads with columnstore, rowstore, and cloud-native architecture
Build fast transactions and current analytics on one engine with clear patterns you can run in production.
Teams need live data for applications and up to the minute analytics without a maze of replicas and exports. Split architectures slow you down and hide failure paths.
This book shows a practical path on SingleStore, from first table to stable operations. You will design schemas that fit both point reads and large scans, choose shard keys that keep joins local, and size partitions and workspaces for predictable latency and throughput.
when to use rowstore and when to use columnstore, with costs, access patterns, and sort key choices that improve data skippinghow universal storage and unlimited storage work, including checkpoints, logs, and point in time recovery for real incidentspartition math per leaf, shard key patterns that make joins local, reference tables for small dimensions, and safe reshardingpipelines from s3 azure blob and gcs with schema inference, kafka sources and sinks, offsets, retries, and exactly once patternsapache iceberg read and write workflows that connect your lake and your operational datacompiled and vectorized execution, what explain and visual explain show, and plan regression checks that prevent surprisesindexing for speed, hash and skiplist in rowstore, columnstore keys for selective filtersworkload manager queues and pools, connection limits and thread pools, aggregator sizing, and multi workspace isolationvector type and ann indexes with ivf and hnsw, hybrid search that combines bm25 with vector re rankkai mongo api collection mapping and vectorsearch, plus a simple rag path on singlestorejson functions and computed columns, geospatial types and indexes, and guardrails for semi structured datasecurity end to end, authentication and rbac for least privilege, private networking with privatelink, encryption in transit and at rest, customer managed keys, auditing and access reviewsdeployments with kubernetes operator and helm, helios workspaces as code with terraform, observability with studio and external monitorscost control and sizing levers, autoscaling and stop or start policies for managed workspacesmigration playbooks for mysql and oracle with cdc, schema mapping, dual write windows, and cutover drillsincident drills for lock waits and queue pressure, recovery steps, and a performance hardening preflightThis is a code heavy guide. SQL, Python, Shell, YAML, and JSON snippets map directly to tables, pipelines, backups, recovery steps, and deployment commands you can run in a sandbox and then in production.
Get the blueprint for a dependable HTAP platform, and grab your copy today.
Teams need live data for applications and up to the minute analytics without a maze of replicas and exports. Split architectures slow you down and hide failure paths.
This book shows a practical path on SingleStore, from first table to stable operations. You will design schemas that fit both point reads and large scans, choose shard keys that keep joins local, and size partitions and workspaces for predictable latency and throughput.
when to use rowstore and when to use columnstore, with costs, access patterns, and sort key choices that improve data skippinghow universal storage and unlimited storage work, including checkpoints, logs, and point in time recovery for real incidentspartition math per leaf, shard key patterns that make joins local, reference tables for small dimensions, and safe reshardingpipelines from s3 azure blob and gcs with schema inference, kafka sources and sinks, offsets, retries, and exactly once patternsapache iceberg read and write workflows that connect your lake and your operational datacompiled and vectorized execution, what explain and visual explain show, and plan regression checks that prevent surprisesindexing for speed, hash and skiplist in rowstore, columnstore keys for selective filtersworkload manager queues and pools, connection limits and thread pools, aggregator sizing, and multi workspace isolationvector type and ann indexes with ivf and hnsw, hybrid search that combines bm25 with vector re rankkai mongo api collection mapping and vectorsearch, plus a simple rag path on singlestorejson functions and computed columns, geospatial types and indexes, and guardrails for semi structured datasecurity end to end, authentication and rbac for least privilege, private networking with privatelink, encryption in transit and at rest, customer managed keys, auditing and access reviewsdeployments with kubernetes operator and helm, helios workspaces as code with terraform, observability with studio and external monitorscost control and sizing levers, autoscaling and stop or start policies for managed workspacesmigration playbooks for mysql and oracle with cdc, schema mapping, dual write windows, and cutover drillsincident drills for lock waits and queue pressure, recovery steps, and a performance hardening preflightThis is a code heavy guide. SQL, Python, Shell, YAML, and JSON snippets map directly to tables, pipelines, backups, recovery steps, and deployment commands you can run in a sandbox and then in production.
Get the blueprint for a dependable HTAP platform, and grab your copy today.
289 pages, Kindle Edition
Published November 1, 2025
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