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Materialized Views

38 articles · Page 1 of 1
Xiaolin Talks Programming
Xiaolin Talks Programming
Sep 5, 2026 · Backend Development

Migrating Log Platform from Elasticsearch to ClickHouse: Table Design, Materialized Views & Tuning Lessons

The author details migrating a high-volume logging platform from Elasticsearch to ClickHouse, covering schema design with ReplicatedMergeTree, Spring Boot integration via JDBC and MyBatis, materialized views for pre-aggregation, and optimization techniques like skip indexes, batch inserts, and capacity planning.

ClickHouseElasticsearchKafka
0 likes · 21 min read
Migrating Log Platform from Elasticsearch to ClickHouse: Table Design, Materialized Views & Tuning Lessons
dbaplus Community
dbaplus Community
Aug 30, 2026 · Databases

Why OFFSET Pagination Slows You Down: Switch to Keyset and Cut Latency from Seconds to Milliseconds

The article recounts how an API that originally used OFFSET pagination suffered 2‑3 seconds response time, and after rewriting the query to Keyset (Seek) pagination—adding a secondary sort key for stability and exploring cursor pagination, index‑only OFFSET, and materialized views—the same endpoint now responds in under 200 ms, with detailed benchmark comparisons.

Cursor PaginationMaterialized ViewsPerformance Optimization
0 likes · 7 min read
Why OFFSET Pagination Slows You Down: Switch to Keyset and Cut Latency from Seconds to Milliseconds
Xiaolin Talks Programming
Xiaolin Talks Programming
Aug 9, 2026 · Big Data

Spring Boot + Apache Doris: Real-Time Data Warehousing Pitfalls and OLAP Optimization

This article shares production lessons from integrating Spring Boot with Apache Doris for real-time data warehousing, covering connection pool tuning, data model selection, ingestion methods, materialized views, Colocate Join optimization, resource isolation, compaction tuning, BI tool integration, and cluster operations.

Apache DorisCluster OperationsColocate Join
0 likes · 16 min read
Spring Boot + Apache Doris: Real-Time Data Warehousing Pitfalls and OLAP Optimization
StarRocks
StarRocks
Mar 11, 2026 · Databases

How StarRocks Supercharges Real‑Time Ad Funnel Monitoring and Creative Optimization

This article dissects the full advertising funnel, explains why CTR and eCPM are critical, and demonstrates how StarRocks combined with Flink can deliver minute‑level real‑time monitoring, material selection, anomaly alerts, A/B testing, and a successful migration from Druid for massive ad‑tech workloads.

AdvertisingMaterialized ViewsReal-time Analytics
0 likes · 20 min read
How StarRocks Supercharges Real‑Time Ad Funnel Monitoring and Creative Optimization
Senior Xiao Ying
Senior Xiao Ying
Feb 18, 2026 · Databases

Beyond SELECT: Creating, Optimizing, and Securing MySQL Views and Materialized Views

This article explains MySQL view fundamentals, outlines update limitations, demonstrates INSTEAD OF triggers and stored procedures as workarounds, details two methods for simulating materialized views—including scheduled table refreshes and trigger‑based real‑time updates—covers optimization techniques, and shows role‑based permission management for both regular and materialized views.

Materialized ViewsMySQLOptimization
0 likes · 13 min read
Beyond SELECT: Creating, Optimizing, and Securing MySQL Views and Materialized Views
StarRocks
StarRocks
Dec 18, 2025 · Databases

How Fresha Scaled Real‑Time Analytics with StarRocks: A Deep Dive into Their Hybrid Architecture

Facing Postgres overload and costly Snowflake queries, Fresha rebuilt its analytics platform by introducing StarRocks as a unified SQL entry point, combining federated lakehouse queries with high‑performance internal tables, which reduced homepage query latency to around 200 ms and achieved minute‑level data freshness across real‑time, historical, and search workloads.

Compute-Storage SeparationData PipelineHybrid Architecture
0 likes · 20 min read
How Fresha Scaled Real‑Time Analytics with StarRocks: A Deep Dive into Their Hybrid Architecture
Big Data Technology & Architecture
Big Data Technology & Architecture
Sep 10, 2025 · Databases

When to Use Materialized Views in Production: Benefits, Types, and Pitfalls

This article explains what materialized views are, outlines their advantages such as query acceleration, lightweight ETL, and lake‑warehouse integration, classifies them by sync mode, table count, and refresh strategy, and highlights their limitations and best‑practice recommendations for production use.

Data WarehousingETLMaterialized Views
0 likes · 6 min read
When to Use Materialized Views in Production: Benefits, Types, and Pitfalls
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 5, 2025 · Big Data

How StarRocks + Paimon Powered Real‑Time Analytics for Alibaba’s Taobao Flash Sale

Facing minute‑level decision demands and billions of marketing events during Taobao's Flash Sale, the Ele.me data team built a real‑time lakehouse with StarRocks and Paimon, leveraging asynchronous materialized views, RoaringBitmap de‑duplication, and resource isolation to achieve sub‑second query latency, lower storage costs, and stable high‑concurrency.

LakehouseMaterialized ViewsPaimon
0 likes · 25 min read
How StarRocks + Paimon Powered Real‑Time Analytics for Alibaba’s Taobao Flash Sale
StarRocks
StarRocks
Sep 2, 2025 · Big Data

How StarRocks + Paimon Powered Real‑Time Analytics for Alibaba’s Flash Sale

Faced with billions of marketing events and minute‑level decision requirements during Taobao's flash‑sale campaign, the e‑commerce data team built a real‑time lakehouse using StarRocks and Paimon, leveraged asynchronous materialized views and RoaringBitmap deduplication, and achieved sub‑second query latency, massive cost savings, and stable high‑concurrency performance.

LakehouseMaterialized ViewsPaimon
0 likes · 26 min read
How StarRocks + Paimon Powered Real‑Time Analytics for Alibaba’s Flash Sale
StarRocks
StarRocks
Apr 24, 2025 · Databases

Inside StarRocks Optimizer: Architecture, Multi‑Stage Optimization, and Advanced Features

This article provides a comprehensive technical overview of StarRocks' query optimizer, covering its evolution, core architecture, multi‑stage optimization pipeline, key optimizations such as multi‑join colocate, low‑cardinality global dictionary, MV union rewrite, and advanced mechanisms like cost‑estimation fixes, query feedback, adaptive execution, runtime filters, join‑reorder strategies, and SQL plan management.

Cost-Based OptimizationMaterialized ViewsOLAP
0 likes · 26 min read
Inside StarRocks Optimizer: Architecture, Multi‑Stage Optimization, and Advanced Features
DataFunTalk
DataFunTalk
Dec 25, 2024 · Databases

Applying RisingWave to Real-Time Feature Engineering: Architecture, Capabilities, and Use Cases

This article introduces RisingWave, an open‑source streaming database, and explains how its SQL‑based interface, compute‑storage separation, UDF support, and materialized views enable efficient real‑time feature engineering, state management, and diverse downstream applications, including the enhancements in RisingWave 2.0.

Materialized ViewsReal-time Feature EngineeringRisingWave
0 likes · 17 min read
Applying RisingWave to Real-Time Feature Engineering: Architecture, Capabilities, and Use Cases
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 21, 2024 · Big Data

Key New Features of Apache Doris 3.0: Storage‑Compute Separation, Lakehouse Integration, Semi‑Structured Data, ETL Enhancements, Materialized Views, and Java UDTF

Apache Doris 3.0 introduces storage‑compute separation, native lakehouse write‑back, optimized Variant handling for semi‑structured data, stronger ETL transaction support, enhanced multi‑table materialized views, and Java UDTF capabilities, providing developers with more flexible, cost‑effective, and high‑performance analytics solutions.

Apache DorisETLJava UDTF
0 likes · 7 min read
Key New Features of Apache Doris 3.0: Storage‑Compute Separation, Lakehouse Integration, Semi‑Structured Data, ETL Enhancements, Materialized Views, and Java UDTF
StarRocks
StarRocks
Jun 6, 2024 · Big Data

Why StarRocks Beats Trino: A Deep Technical Comparison

This article provides a detailed technical comparison between StarRocks and Trino, covering their shared MPP architecture, cost‑based optimizer, pipeline execution, ANSI SQL support, differences in vectorized execution, materialized view capabilities, caching systems, data source connectors, benchmark results, high‑availability designs, join algorithms, and real‑world user case studies.

MPPMaterialized ViewsStarRocks
0 likes · 20 min read
Why StarRocks Beats Trino: A Deep Technical Comparison
Airbnb Technology Team
Airbnb Technology Team
Mar 1, 2024 · Big Data

Riverbed: A Scalable Data Framework for Real‑time and Batch Processing at Airbnb

Airbnb’s Riverbed framework unifies streaming CDC events and batch Spark jobs behind a GraphQL‑based declarative API to automatically build and maintain distributed materialized views, using Kafka‑partitioned ordering and version control to deliver billions of daily updates with low‑latency reads for features such as payments and search.

AirbnbApache SparkKafka
0 likes · 8 min read
Riverbed: A Scalable Data Framework for Real‑time and Batch Processing at Airbnb
Didi Tech
Didi Tech
Feb 27, 2024 · Big Data

Real-time Precise Deduplication Using StarRocks Materialized Views at Didi

Didi leverages StarRocks materialized views with a global dictionary and bitmap aggregation to perform real‑time, high‑cardinality precise deduplication, automatically rewriting queries and refreshing views, cutting query latency by ~80%, reducing resource use ~95%, and boosting concurrent QPS up to 100‑fold, while planning further automation and bitmap optimizations.

Materialized ViewsOLAPPrecise Deduplication
0 likes · 19 min read
Real-time Precise Deduplication Using StarRocks Materialized Views at Didi
StarRocks
StarRocks
Feb 27, 2024 · Databases

How StarRocks Materialized Views Enable High‑Concurrency Precise Deduplication

StarRocks’ materialized view feature lets Didi replace costly fuzzy deduplication with precise, high‑concurrency deduplication for real‑time dashboards, using global dictionary mapping, layered ODS/DWD/ADS views, synchronous and asynchronous refreshes, and transparent query rewrite to cut query latency by 80% and boost QPS dramatically.

Materialized ViewsOLAPPrecise Deduplication
0 likes · 20 min read
How StarRocks Materialized Views Enable High‑Concurrency Precise Deduplication
Sohu Tech Products
Sohu Tech Products
Jan 31, 2024 · Industry Insights

How Didi Scaled Real‑Time Dashboards with StarRocks Materialized Views

This article details Didi's evolution from a multi‑engine OLAP stack to a unified StarRocks solution, explains the design of global dictionaries and materialized views for real‑time dashboard acceleration, and shares performance results, challenges, and future optimization directions.

DidiMaterialized ViewsOLAP
0 likes · 19 min read
How Didi Scaled Real‑Time Dashboards with StarRocks Materialized Views
Past Memory Big Data
Past Memory Big Data
Jan 17, 2024 · Big Data

How WeChat Implements a StarRocks‑Powered Lakehouse Across Multiple Business Scenarios

WeChat evolved its data platform from Hadoop to ClickHouse and finally to a StarRocks‑based lakehouse, solving data fragmentation and storage redundancy while achieving sub‑second to minute‑level query latency, cutting storage costs by over 65%, halving operational tasks, and reducing offline job time by two hours across several business lines.

LakehouseMaterialized ViewsReal-time Analytics
0 likes · 16 min read
How WeChat Implements a StarRocks‑Powered Lakehouse Across Multiple Business Scenarios
DataFunSummit
DataFunSummit
Dec 7, 2023 · Databases

Apache Doris: A High‑Performance Real‑Time Analytical Database for Online High‑Concurrency Reporting

This article introduces Apache Doris, a real‑time analytical database built on an MPP architecture, explains its suitability for massive data workloads and online high‑concurrency reporting scenarios, and details the core technologies—storage models, vectorized query engine, materialized views, partitioning, indexing, row‑store and prepared statements—that enable sub‑second query latency and high QPS, while also showing a real‑world case study and how to join the Doris community.

Apache DorisHigh ConcurrencyMaterialized Views
0 likes · 13 min read
Apache Doris: A High‑Performance Real‑Time Analytical Database for Online High‑Concurrency Reporting
StarRocks
StarRocks
Nov 23, 2023 · Databases

How StarRocks Redefines Lakehouse Architecture with Compute‑Storage Separation

StarRocks, an open‑source MPP analytical database, consolidates BI, interactive, and real‑time analytics into a single engine by evolving from version 1.0 to 3.x, introducing compute‑storage separation, unified catalog, generated columns, operator spill, and advanced materialized views, while outlining its cloud‑native lakehouse roadmap.

Compute-Storage SeparationLakehouseMPP database
0 likes · 22 min read
How StarRocks Redefines Lakehouse Architecture with Compute‑Storage Separation
StarRocks
StarRocks
Nov 3, 2023 · Databases

How StarRocks’ Spill to Disk Boosts Query Stability and Performance

StarRocks introduces a spill-to-disk mechanism that writes intermediate results of heavy operators to disk, freeing memory and enabling stable execution of ETL and ad‑hoc queries, while combined with materialized views it dramatically improves query success rates and delivers up to 4.35× faster performance than Spark.

Database OptimizationMaterialized ViewsSpill
0 likes · 10 min read
How StarRocks’ Spill to Disk Boosts Query Stability and Performance
StarRocks
StarRocks
Aug 9, 2023 · Databases

StarRocks 3.1 Highlights: Faster Lakehouse Analytics and Advanced Materialized Views

StarRocks 3.1 introduces a cloud‑native, lakehouse‑oriented architecture with enhanced storage‑compute separation, up to 3‑6× faster data‑lake queries than Trino/Presto, expanded Iceberg and Paimon support, richer materialized view capabilities, new random bucketing, expression partitioning, generated columns, and spill‑to‑disk stability, all backed by extensive performance optimizations and open‑source contributions.

Data LakeLakehouseMaterialized Views
0 likes · 17 min read
StarRocks 3.1 Highlights: Faster Lakehouse Analytics and Advanced Materialized Views
StarRocks
StarRocks
Jun 29, 2023 · Big Data

How StarRocks Boosted Mango TV’s Data Platform Performance by Over 10×

Mango TV replaced its fragmented EMR‑Hive‑Kudu‑Presto stack with a unified StarRocks lakehouse, simplifying architecture, cutting operational costs, and achieving more than a ten‑fold increase in query speed while supporting real‑time analytics, materialized views, bitmap indexing, and store‑compute separation.

Bitmap IndexMaterialized ViewsStarRocks
0 likes · 14 min read
How StarRocks Boosted Mango TV’s Data Platform Performance by Over 10×
DataFunSummit
DataFunSummit
May 27, 2023 · Big Data

Building and Practicing the Performance Assurance System of YouShu BI

This article presents an in‑depth overview of the YouShu BI product, outlines the high‑concurrency performance challenges faced by enterprise BI, and details the multi‑layer performance architecture—including front‑end, back‑end, data engine, and data source layers—along with smart caching, MPP acceleration, materialized views, and the Data Doctor operations that together ensure low‑latency, reliable analytics for large‑scale users.

BIMPPMaterialized Views
0 likes · 16 min read
Building and Practicing the Performance Assurance System of YouShu BI
DataFunTalk
DataFunTalk
May 17, 2023 · Databases

Evolution of 360 Commercial Real-Time Data Warehouse and Apache Doris Deployment

This article details the three‑stage evolution of 360's real‑time data warehouse—from Storm + Druid + MySQL to Flink + Druid + TiDB and finally to Flink + Apache Doris—explaining architectural pain points, the reasons for choosing Doris, and how the new system delivers sub‑second query latency, strong consistency, and simplified operations across advertising scenarios.

Apache DorisData ConsistencyFlink
0 likes · 17 min read
Evolution of 360 Commercial Real-Time Data Warehouse and Apache Doris Deployment
DataFunTalk
DataFunTalk
Feb 4, 2023 · Big Data

Design and Practice of Tencent Lighthouse Fusion Analysis Engine

This article presents the design and implementation of Tencent Lighthouse's Fusion Analysis Engine, covering its background, challenges, fusion architecture, kernel optimizations, acceleration techniques, practical outcomes, and future evolution directions for high‑performance data access.

Fusion EngineLighthouseMaterialized Views
0 likes · 12 min read
Design and Practice of Tencent Lighthouse Fusion Analysis Engine
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 26, 2022 · Big Data

ByteDance's Internal Presto OLAP Engine: Deployment, Performance Boosts, and Operational Practices

The article details ByteDance's large‑scale deployment of the Presto OLAP engine for ad‑hoc, BI, and near‑real‑time analytics, describing its architecture, multi‑coordinator high‑availability design, routing gateway, adaptive cancel, history server, materialized‑view support, Hudi connector integration, and how these innovations improve performance, stability, and operational efficiency.

Hudi ConnectorMaterialized ViewsOLAP
0 likes · 11 min read
ByteDance's Internal Presto OLAP Engine: Deployment, Performance Boosts, and Operational Practices
ITPUB
ITPUB
Apr 8, 2022 · Big Data

How to Build a Billion-Scale Real-Time Data Warehouse with ClickHouse

This article explains how a large‑scale advertising platform replaced its slow offline data‑warehouse with a ClickHouse‑based real‑time warehouse, covering data source integration, performance comparison, materialized views, projections, schema management, and cost‑effective hot‑cold storage strategies.

ClickHouseKafka IntegrationMaterialized Views
0 likes · 19 min read
How to Build a Billion-Scale Real-Time Data Warehouse with ClickHouse
Volcano Engine Developer Services
Volcano Engine Developer Services
Dec 29, 2021 · Big Data

Scaling Presto at ByteDance: Architecture, Performance & Stability

ByteDance’s internal Presto platform, supporting nearly one million daily queries across ad‑hoc, BI visualization, and near‑real‑time analytics, achieves high performance and stability through SparkSQL compatibility, multi‑Coordinator architecture, dynamic routing, adaptive query cancellation, History Server, materialized views, and a dedicated Hudi connector.

Distributed SQLHudi ConnectorMaterialized Views
0 likes · 11 min read
Scaling Presto at ByteDance: Architecture, Performance & Stability
Kuaishou Tech
Kuaishou Tech
Aug 30, 2021 · Databases

ClickHouse Projection: Design, Implementation, and Production Performance

This article presents an in‑depth overview of ClickHouse Projection, covering its background, definition, practical use cases, underlying architecture, query analysis, consistency guarantees, performance comparisons, and real‑world production results, highlighting how it enhances OLAP workloads while maintaining strong data consistency.

ClickHouseDatabase OptimizationMaterialized Views
0 likes · 19 min read
ClickHouse Projection: Design, Implementation, and Production Performance
Tencent Cloud Developer
Tencent Cloud Developer
Oct 20, 2020 · Databases

ClickHouse: Architecture, Core Features, and Limitations for Interactive Analytics

ClickHouse is a PB‑scale, open‑source columnar OLAP database that uses a ZooKeeper‑coordinated sharded cluster, columnar storage, vectorized execution, advanced compression, data‑skipping indexes, and materialized views to deliver high‑performance interactive analytics, yet it requires manual shard management, lacks a mature MPP optimizer, and handles real‑time single‑row writes poorly.

ClickHouseDistributed ArchitectureMaterialized Views
0 likes · 18 min read
ClickHouse: Architecture, Core Features, and Limitations for Interactive Analytics
Efficient Ops
Efficient Ops
Jul 24, 2015 · Databases

What MySQL 5.7 InnoDB Experts Reveal: Key Q&A on New Features

An expert panel from the High‑Efficiency Operations community answers eleven pressing MySQL 5.7 questions, covering test hardware, GA timeline, GIS speed, virtual column indexing, materialized view plans, 2‑D geo support, performance monitoring, Oracle’s market strategy, geojson handling, multi‑source replication, buffer‑pool locking, and InnoDB Memcached consistency.

GISInnoDBMaterialized Views
0 likes · 7 min read
What MySQL 5.7 InnoDB Experts Reveal: Key Q&A on New Features