Data integrity
Strict ACID transactions, advanced constraints, custom types and validation rules protect the consistency of business data.
Expertise · PostgreSQL
PostgreSQL Consulting: Performance, High Availability and Migration
Etixio’s PostgreSQL expertise helps you build a relational database that stays consistent, fast and operable as the product and its data evolve. We handle data modeling, optimization, high availability and migration, as well as vector search with pgvector for your AI features.
Understanding the technology
PostgreSQL in your project.
PostgreSQL is a relational database that lets you define structures, constraints and transactions for an application’s data. It also offers capabilities suited to different types of data. We start from the business model and the expected queries to organize how it is used.
The benefits for your application
Why choose PostgreSQL?
PostgreSQL is an open-source relational database known for its rigor and extensibility. It suits business applications, multi-tenant SaaS platforms and analytical workloads, and can also store semi-structured or vector data.
Advanced SQL features
Window functions, CTEs and recursive queries, indexable JSONB, full-text search and materialized views.
Extensibility
Extensions such as PostGIS, TimescaleDB or pgvector, procedural functions and languages (PL/pgSQL, PL/Python), foreign data wrappers.
Performance
Cost-based optimizer, parallel queries, native partitioning and a wide choice of index types.
Standards compliance
A high level of SQL compliance that makes portability and integration with ecosystem tools easier.
What we cover
The work we take on.
Schema
Define relationships, constraints and transactions.
Performance
Review queries, indexes and processing based on data volumes.
Maintenance
Organize migrations, backups and service monitoring.
Our PostgreSQL expertise
The PostgreSQL ecosystem we master.
PostgreSQL core
Recent PostgreSQL versions, B-tree, GiST, GIN, SP-GiST and BRIN indexes, query planner, parallel execution and logical replication.
Extensions
PostGIS for geographic data, TimescaleDB for time series, pgvector for similarity search on embeddings.
High availability
Synchronous or asynchronous streaming replication, Patroni for automatic failover, pgBackRest for incremental backups and point-in-time recovery.
Performance & monitoring
pg_stat_statements, EXPLAIN ANALYZE, configuration and vacuum tuning, PgBouncer for connection pooling.
PostgreSQL and AI
Vector search in your existing database.
With the pgvector extension, PostgreSQL stores the embeddings of your documents and answers similarity searches, alongside business data and its access rights. It is often the simplest way to add document search or an assistant to an existing product, without introducing an additional database.
We design document chunking, vector indexes, filtering by customer or permission and embedding updates, then measure the quality of the results. See our AI solutions for business, our AI agents and chatbots and our BI & data offering.
In the field
From technology to real-world use.
In a multi-tenant application, the schema and access rules must keep information consistently separated. We define the constraints, migrations and tests that verify critical operations. Slowdowns are investigated from the queries and their plans, rather than fixed only by adding resources.
The choices that matter
The choices to examine before building.
Indexes, long-running transactions and concurrent access can change behavior under load. We measure key user flows and review maintenance operations. A backup must come with a tested restore scenario, with a clear understanding of recovery time and recoverable data.
From work to deliverables
Delivered work your team can take over.
The scope of the engagement specifies the components to build or take over and the acceptance criteria. We prepare what is needed to understand the changes, verify them and continue the work.
- Documented data model
- Migrations and integration tests
- Data access and query analysis
Frequently asked questions
PostgreSQL: your questions.
What is PostgreSQL and why use it?
PostgreSQL is an open-source relational database that is feature-rich, extensible and close to the SQL standard. It suits critical applications, SaaS platforms and analytical needs that require consistency and scalability.
Is PostgreSQL suitable for enterprise applications?
Yes. ACID transactions, fine-grained security (roles, row-level security), high availability and extensions make it well suited to critical applications. Specialized vendors also offer commercial support.
What is the difference between PostgreSQL and MySQL?
PostgreSQL offers more features, more extensibility and stricter SQL compliance, useful for complex data and analytics. MySQL is easy to operate and efficient for read-heavy web applications.
How do you optimize PostgreSQL performance?
Appropriate indexes (B-tree, GIN, GiST), query analysis with EXPLAIN ANALYZE and pg_stat_statements, configuration (work_mem, shared_buffers) and vacuum tuning, partitioning and connection pooling.
Which PostgreSQL extensions are the most useful?
PostGIS for geographic data, TimescaleDB for time series, pgvector for vector search, pg_stat_statements for performance, as well as custom functions and procedural languages.
How do you scale a PostgreSQL database?
Read replicas, native partitioning, connection pooling with PgBouncer, sharding with Citus for very large volumes, or managed services such as Amazon RDS or Google Cloud SQL. The architecture depends on the actual load.
Is PostgreSQL suitable for data analytics?
Yes, with window functions, CTEs, materialized views, JSONB and foreign data wrappers. For very large analytical volumes, a dedicated data warehouse can complement the database.
Can PostgreSQL replace a NoSQL database?
Often, yes. Indexable JSONB makes it possible to store semi-structured documents while keeping transactions and joins. A document database such as MongoDB remains relevant for certain models and distribution needs.
Can PostgreSQL be used for AI search?
Yes, with pgvector. Embeddings are stored alongside business data, which makes it possible to filter results according to each user’s permissions. We set up indexing, embedding updates and result evaluation before the production release.
What collaboration models do you offer?
A fixed-price project for a defined architecture, migration or optimization, a dedicated team to evolve the application and its data over time, or a targeted engagement (performance, extension development, incident).
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the initial scope of work with your team.