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Training TimescaleDB 2026 - Optimizing Massive Time-Series Data

Ref: YVM381
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master advanced hypertables in TimescaleDB 2026 for managing massive time-series data volumes
  • Develop automated retention and compression policies to optimize enterprise storage and performance
  • Design continuous aggregates for ultra-high-performance real-time analytics
  • Implement advanced jobs and custom triggers
  • Optimize spatial and multi-node queries for scalable projects
  • Deploy TimescaleDB 2026 in production with high availability and expert monitoring

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1TimescaleDB 2026 Hypertables: Expert Creation and Management (chunks, policies, advanced partitioning)

Dive into creating optimized hypertables for terabytes of time-series data, configure intelligent chunks with multi-dimensional partitioning strategies, implement automated compression policies to reduce storage costs by 90%, perform practical exercises on real IoT datasets, test scalability by simulating high-frequency data streams, and produce a first deliverable: a performant hypertable schema with benchmark metrics.

Module 2TimescaleDB 2026: Continuous Aggregates and Materialized Views (real-time queries, refresh policies)

Explore next-generation continuous aggregates for latency-free real-time dashboards, configure adaptive refresh policies based on usage, integrate custom UDFs for complex aggregations, apply to real-world massive application logs, optimize performance with hints and advanced GIN indexes, conduct hands-on workshops to validate scalable materialized views, and generate a measurable optimization report.

Module 3TimescaleDB 2026 Jobs and Triggers: Expert Automation (scheduling, data retention, alerting)

Master advanced jobs for automating recurring tasks like selective retention and incremental backups, deploy custom triggers for real-time event-driven workflows, integrate Slack/Email notifications via pg_cron extensions, simulate maintenance scenarios on distributed clusters, test resilience with simulated downtimes, conduct collaborative exercises for automated ETL pipelines, and deliver a complete job script with integrated monitoring.

Module 4TimescaleDB 2026 Query Optimization: Spatial and Multi-Node (hypercore, sharding, PostGIS)

Optimize spatial queries with the PostGIS-Timescale extension for geolocation use cases, configure multi-node hypercore for infinite horizontal scalability, analyze EXPLAIN plans focusing on time_bucket and gapfill, apply intelligent sharding techniques to global datasets, run comparative benchmarks vs. Cassandra/InfluxDB, practice on real DevOps cases with Grafana, and produce a query optimization guide with quantified performance gains.

Module 5TimescaleDB 2026 Production Deployment: HA, Monitoring, and Security (Kubernetes, Patroni, pgBadger)

Deploy in production with high availability using Patroni and dedicated Kubernetes operators, integrate advanced monitoring with Prometheus and pgBadger for proactive alerts, secure access with row-level security and at-rest encryption, simulate live failovers and recoveries, configure WAL-E backups for zero RPO, complete with a capstone project on a multi-AZ cluster, and earn certification with an enterprise-ready portfolio of deliverables.

Evaluation method

  • Daily technical quizzes on expert concepts
  • Practical pair project with source code and benchmarks
  • Final certifying exam with real-world cases and advanced multiple-choice questions

Learning method

  • Project-based methodology inspired by real industrial production scenarios
  • 70% hands-on exercises on dedicated environments
  • Case studies from Fortune 500 companies using TimescaleDB
  • 3-month post-training support with lab access and coaching

Methods, materials and delivery

The Training TimescaleDB 2026 - Optimizing Massive Time-Series Data program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training TimescaleDB 2026 - Optimizing Massive Time-Series Data program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training TimescaleDB 2026 - Optimizing Massive Time-Series Data program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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