
Open-Source Database Program
Runs PostgreSQL, MySQL, and Redis reliably, often as a move away from licensed databases

Relational, NoSQL, cloud warehouses, and vector stores: one partner for every database your teams run.
42 instructor-led programs covering relational administration, NoSQL engineering, cloud data warehousing, and AI data infrastructure, scoped to the engines your teams actually run.
Instructor-led workshops and programsIn-house, virtual or blended10+ languagesDelivered in English, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian, and more100+ countriesWe have delivered in United States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
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Databases training is instructor-led group training that builds an organization's ability to design, run, and modernize the data platforms its products and analytics depend on. It spans relational administration (Oracle, SQL Server, PostgreSQL, MySQL), NoSQL and in-memory stores (MongoDB, Cassandra, Redis, Elasticsearch), cloud data warehousing (Snowflake, Redshift, Teradata), and the vector and graph databases behind AI applications. Programs are scoped to the engines and workloads a team actually runs and delivered to a closed cohort rather than sold as individual seats.
The commercial distinction is between having databases and running them well. Downtime, slow queries, and fragile migrations cost real revenue; group training builds shared practice: the same administration discipline, the same performance tuning habits, and the same migration playbook across DBAs, platform engineers, and developers. For data-driven organizations, that shared practice is what keeps the data layer reliable.
The program covers the database landscape end to end: SQL language fundamentals through advanced querying, relational administration and high availability, NoSQL engineering across document, wide-column, cache, time-series and search stores, cloud migration and modernization, and AI data infrastructure with vector and graph databases. Built for DBAs, platform engineers, data engineers, and developers who carry the daily responsibility for data availability and performance.
Every engagement starts with discovery: which engines, which workloads, which migration or modernization pressures, and which teams carry them. Trainers are then matched from a vetted bench of database practitioners, and the program is tailored before delivery. Cohorts are closed to your organization, run in your timezone, and measured with pre- and post-assessments so L&D can show what changed.
Six areas carry most of the catalog. Start where your needs are greatest.
Databases programs to start with.
Deploy, secure, monitor and tune Azure SQL Database and Managed Instance.
Design DynamoDB tables around access patterns, and manage keys, indexes, capacity and streams.
Load, distribute, sort and query data in Redshift clusters, and keep costs and query times under control.
Model entities and relationships as graphs and ontologies, and decide where a knowledge graph fits your data.
42 instructor-led programs across six database topics. Filter by topic, search the live catalog, and every program is delivered as a closed cohort scoped to your engines.
SHOWING 1–15 OF 42 · 42 IN THE LIVE CATALOG
Deploy, secure, monitor and tune Azure SQL Database and Managed Instance.
Design DynamoDB tables around access patterns, and manage keys, indexes, capacity and streams.
Load, distribute, sort and query data in Redshift clusters, and keep costs and query times under control.
Model data by query, run multi-node Cassandra clusters, and manage replication and consistency.
Design HBase tables and row keys, and serve fast reads and writes on Hadoop data.
Launch, back up, patch, scale and monitor managed databases on Amazon RDS.
Install, manage and tune Greenplum clusters, including segments, distribution and workload management.
Model documents, query with SQL++ and run Couchbase clusters.
Set up CouchDB, model documents, write views and set up replication.
Set performance baselines, plan capacity, handle backups and failover, and fix slow queries across your databases.
Index documents, write queries and aggregations, and manage Elasticsearch clusters for search and logs.
Assess, plan and execute database migrations with schema conversion, data validation and a tested cutover.
Build logical and physical data models in ERwin and generate database schemas.
Model entities and relationships as graphs and ontologies, and decide where a knowledge graph fits your data.
Store, query and downsample time series metrics in InfluxDB, with retention policies that control growth.
Build your team’s capabilities in databases with curated training programs arranged in a clear learning sequence. Each pathway builds skills progressively, helping your workforce achieve defined milestones and apply their learning to business goals.

Runs PostgreSQL, MySQL, and Redis reliably, often as a move away from licensed databases
Install, configure and administer MySQL and MariaDB for performance, security and recovery
Engineer database reliability: capacity planning, performance tuning, failover and migration

Gives analysts and engineers direct, correct access to data
Use SQL for business analytics: querying, joins, window functions, CTEs and reporting from relational databases.
Write Oracle SQL and PL/SQL: complex queries, stored procedures, triggers and performance tuning.

Builds skill in document, wide-column, cache, time-series, and search databases
Operate Apache Cassandra: data modelling, CQL, replication strategies, compaction and cluster operations.
Manage time-series data with InfluxDB: schema design, Flux queries, retention policies and dashboarding.
Deploy and query Elasticsearch: index design, mappings, aggregations, relevance tuning and cluster management.

Plans and executes database moves to the cloud with minimal downtime
Replicate and stream data changes in real time with Oracle GoldenGate across heterogeneous databases
Engineer database reliability: capacity planning, performance tuning, failover and migration

Builds the vector, graph, and search stores behind AI applications
Build and query knowledge graphs: ontology design, graph databases, SPARQL and enterprise integration.
Model and query graph data in Neo4j: Cypher queries, indexing, graph algorithms and application integration.
Deploy and query Elasticsearch: index design, mappings, aggregations, relevance tuning and cluster management.
Explore databases training aligned with your teams’ functions, job roles, industry and tools. Help your teams build the knowledge and practical skills to develop capabilities in databases across your organization, supporting your business priorities and evolving needs.
Keep database services dependable through disciplined operational practices. Explore monitoring, backups, recovery and maintenance so teams can detect problems and rehearse restoration before disruption.
Build application data access that behaves predictably under real workloads. Practice query design, transactions and schema interactions that support correctness as applications evolve.
Apply protection to the ways database information is stored and accessed. Explore least-privilege permissions, encryption and audit evidence while considering the needs of legitimate users.
Plan database changes with compatibility, data quality and continuity in view. Practice migration assessment, validation and cutover planning so teams can identify risks before moving production data.
Design data structures and access patterns that support dependable analysis. Explore modeling, workload performance and data-quality checks around reporting and analytical use cases.
Evaluate database choices against business requirements and system constraints. Compare relational and document approaches, consistency needs and operational tradeoffs to communicate clearer design decisions.
Build confidence in retrieving and checking the data behind an analysis. Practice joins, aggregations and result validation so conclusions rest on understandable queries.
Develop practical skills for working with PostgreSQL data and services. Explore SQL features, indexing and operational fundamentals through workloads relevant to your environment.
Build confidence in managing and improving SQL Server workloads. Explore data protection, query performance and deployment practices suited to your supported platform and version.
Model document data around how applications read and update it. Practice schema choices, relationships and query patterns that balance flexibility with predictable behavior.
Training a role that is not listed, or a mix of them? Tell us who you are training and what they need to do, and we build the shortlist
Where database teams most often cross-train, based on how these courses are classified.
Domain-level outcomes, not course objectives. These are the capabilities enterprises usually buy this training to build.
DBAs and platform engineers who can keep Oracle, SQL Server, PostgreSQL, and MySQL estates available, backed up, and patched.
Teams who choose the right store for the workload and operate document, wide-column, cache, time-series, and search databases confidently.
Analysts and engineers who write correct, performant SQL, from foundations through advanced querying and PL/SQL.
Architects and DBAs who plan and execute database moves to the cloud with minimal downtime, using proven migration tooling.
AI and data engineers who can build the vector, graph, and search stores behind retrieval-augmented generation and recommendations.
DBAs who diagnose slow queries, tune indexes, and keep database performance ahead of workload growth.
Teams that treat databases as engineered systems: reliability practices, change control, and observability built in.
Onsite, live virtual, or hybrid, every program is instructor-led and built around your teams.
A trainer comes to your office and works face to face with your team, using your policies and your examples.
For small teams or enterprise-wide training, across one site or multiple global locations, in one language or multiple languages.
Get a QuoteExpert-led live online sessions delivered anywhere, with consistency and easy scheduling. Training tools such as Zoom or Microsoft Teams are selected subject to your organization's approval and compliance requirements.
For small teams or enterprise-wide training, across one site or multiple global locations, in one language or multiple languages.
Get a QuoteCombine in-person sessions with live online training in a coordinated instructor-led program, with the mix planned around your team's needs.
For small teams or enterprise-wide training, across one site or multiple global locations, in one language or multiple languages.
Get a QuoteEdstellar shapes database training around the data structures, workloads and service responsibilities your teams manage. Customized, role-based, instructor-led programs support developers, database administrators and technical leads with practical application in design, querying and operations. Learning connects performance, access and recovery considerations with business requirements, while adapting to changing data models, deployment environments and the demands of new applications over time.

Practice schema, query and access choices against relevant application needs
Build role-specific capabilities across database design, implementation and daily operations
Evaluate performance, access controls and recovery tradeoffs through practical scenarios
Adapt database capabilities as workloads, platforms and deployment environments change
Experience across industries brings business context to database learning
Company-wide training experience informing practical learning for database teams
Company-wide trainer network supporting database learning and complementary business skills
Edstellar's certified quality and information-security management systems support database training delivery
Every engagement runs the same five stages, from capability baseline through delivery to sustained measurement.
We meet your stakeholders and L&D team to baseline what your people can do today against the Databases capability you need.
Weeks 1–2
Programs are assembled against your policies, obligations, and team levels, then trainers are shortlisted from the vetted bench.
Weeks 2–4
Closed-cohort instructor-led sessions in your language and timezone, with labs, exercises, and materials shipped alongside.
Scheduled to your calendar
Pre- and post-assessments establish a measurable change in capability, benchmarked against role frameworks.
Immediately after delivery
Retrospectives, refresher modules and skill-refresh tracking keep the investment from decaying, and the measured gaps feed the next cycle.
Quarterly
Stage 05 feeds the next cycle: the gaps it measures become the next Discover.
Also from Edstellar
Psychometric, behavioral, leadership and 360-degree assessment.
Needs analysis, gap identification, and a training roadmap.
Learning strategy, content, technology and ROI measurement.
Org design, succession planning and cultural change.
Training outsourcing, vendor management, logistics and administration.
Executive and manager coaching that keeps skills in use.
DBAs, platform engineers, data engineers, and developers who build or run data platforms.
Instructor-led and live, as a closed cohort for your team, onsite, virtual, or hybrid. You choose the format, location, language, and schedule.
Yes. Oracle, SQL Server, PostgreSQL, and MySQL administration are core programs, including high availability and performance tuning.
Yes. MongoDB, Cassandra, Redis, Elasticsearch, and InfluxDB are covered, plus Neo4j and graph databases.
Yes. Cloud data warehousing covers Snowflake, Redshift, and Teradata, plus migration and modernization programs.
Yes. Vector databases, semantic search, knowledge graphs, and Neo4j are covered for AI workloads.
Most programs run 20 to 32 hours across several sessions. We schedule around your operations and on-call rotations.
Cohorts run from a single small team up to multi-team rollouts, with one trainer per cohort for discussion quality.
Yes. Every program is tailored to the engines your teams run and the workloads they carry before delivery.
Pre- and post-assessments measure capability change, benchmarked against DBA and data engineering role frameworks.
Yes. Training needs analysis and skills baselining identify exactly which database skills each team needs.
Tell us which engines and workloads your teams run, and we match trainers from a vetted bench of database practitioners.
Pick the scale that matches your rollout. Every quote is tailored to your teams and timeline.
Team size
1–25 PARTICIPANTS
One or two programs for a single team, delivered as a closed cohort. The usual entry point for a first Databases engagement.
26–150 PARTICIPANTS
Multiple cohorts or programs for larger teams, with delivery structured around your workforce and training requirements.
151–1,000 PARTICIPANTS
A coordinated rollout across business units, with role-based tracks and central reporting for L&D.
1,000+ PARTICIPANTS
Databases capability at organizational scale, with dedicated management and measurement from pilot to rollout.
Tell us which teams you are training and what they need to be able to do. Anything you filtered in the catalog comes through with your message.