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ClickHouse 26.8 LTS feature map: cost-based optimizer, parallel GROUP BY, Parquet lazy materialisation, streaming HTTP API and background queries for real-time analytics

ClickHouse 26.8 LTS: The Advanced Features That Change Real-Time Analytics Performance

ChistaDATA · ClickHouse release engineering · September 2026 ClickHouse 26.8 LTS: The Advanced Features That Change Real-Time Analytics Performance ClickHouse 26.8 LTS shipped on 10 September 2026 with 98 new features, 128 performance optimisations and […]

ClickHouse workshop for CTOs and data architects: three-day agenda covering architecture and fit, measured cost, and migration and people decisions

Real-Time Analytics ClickHouse Workshop for CTOs and Data Architects

ChistaDATA Inc.

A three-day ClickHouse workshop for CTOs and data architects from ChistaDATA University: architecture fit, measured cost, rollup design and migration cutover, with real lab output.

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ClickHouse certification and competency ladder at ChistaDATA University: CHT-100 to CHT-300 core levels, CHT-400 and CHT-500 specialist programmes, CHT-900 executive track, and the three certification tiers

ClickHouse Certification at ChistaDATA University: 3 Proven Tiers

ChistaDATA Inc.

How ChistaDATA University builds ClickHouse certification on a competency ladder: CHT-100 to CHT-900 programmes, real lab code, failure drills, a live-cluster capstone defence, corporate and academic delivery, and how to start.

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Real-Time Analytics on ClickHouse 26.8: 6 Proven Levers

ChistaDATA Inc.

Real-time analytics on ClickHouse 26.8: the ingest-to-dashboard latency budget, async-insert freshness, top-K and cache serving, lightweight UPDATE, and ingest/serving isolation on self-managed clusters versus ClickHouse Cloud.

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ClickHouse 26.8 LTS: 7 Essential Performance and HA Changes

ChistaDATA Inc.

ClickHouse 26.8 LTS read for production: adaptive aggregation, IEJoin, plan-based parallel replicas, Keeper on disk, always_fetch_mutated_part, and the 26.3 to 26.8 breaking-change checklist for self-managed and Cloud.

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ClickHouse Real-Time POS Analytics: Sub-Second Decisioning for QSR Enterprises

ChistaDATA Inc.

If you’ve spent any time working in QSR (Quick Service Restaurant) data infrastructure, you already know the problem. The need for ClickHouse real-time POS analytics has never been more urgent — millions of POS transactions […]

multi-region ClickHouse deployment architecture showing distributed cluster replication : Sharding and Resharding Strategies

Designing Multi-Region ClickHouse Deployments for Global Scale: 3 Best Patterns

ChistaDATA Inc.

ClickHouse multi-region deployment is one of the most architecturally demanding problems in distributed analytics. When your users span three continents, a single-region cluster becomes a latency ceiling, a compliance liability, and a single point of […]

ClickHouse Disaster Recovery Drills: Frequency, Scope, and Reporting

ChistaDATA Inc.

ClickHouse disaster recovery drills are structured tests designed to validate your analytical database’s recovery procedures before a real failure occurs. Running regular ClickHouse disaster recovery drills is how engineering teams build confidence that their backup-restore […]

ClickHouse Observability Stack in 2026: Apache Iceberg and OpenTelemetry for Real-Time Telemetry

ChistaDATA Inc.

Over the past few years, our platform engineering team at ChistaDATA has been rethinking how we approach observability infrastructure at scale. The conversation keeps circling back to the same frustration: most organizations are sitting on […]

Vector Database Indexing: HNSW, IVF, PQ, OPQ, and ScaNN Explained

ChistaDATA Inc.

A practitioner’s guide to vector database indexing — HNSW, IVF, PQ, OPQ, and ScaNN. Tuning, trade-offs, and architecture patterns from MinervaDB engineers.

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* Everything changes over time – Our blogs/posts and comments changes over time, That’s how it should be! Whatever we comment from ChistaDATA Inc. Teams (including Shiv Iyer) and other stakeholders or guest bloggers posted here are never permanent, These things worked for us. But, there is no guarantee they will work for you too, When using the recommendations from ChistaDATA or MinervaDB or MinervaSQL or any other online resources / Google, You must test the advice before applying them to your production systems, and always invest for a robust Database DR solution, Thank you for understanding.

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