PostgreSQL Fine-Tuning

If your system is slow, queries are taking forever, and the database bottleneck seems like an unsolvable mystery, you know the pain. PostgreSQL is a robust and powerful database, but to extract its maximum potential, simply “installing and using” it isn’t enough. It requires a meticulous job of PostgreSQL fine-tuning.

The truth is, most IT teams and even in-house DBAs don’t have the time or expertise to delve into the most technical details that make all the difference. And this is exactly where the performance, security, and stability of your database can be compromised.

It’s not about blame, but about focus. Your team is busy with dozens of other responsibilities: infrastructure, development, support. PostgreSQL fine-tuning ends up being neglected. And that’s why medium and large-sized companies trust HTI Tecnologia to take care of their databases 24/7, ensuring they operate at maximum efficiency, without interruptions.

In this article, we will reveal 7 crucial PostgreSQL optimization points that you need to master — and why outsourcing this service might be the most strategic decision your company will make.

The Myth of the “Autonomous” PostgreSQL: Why Tuning is Indispensable

Many believe that PostgreSQL, being open-source software, adjusts itself. But this is far from true. Each application has a unique load behavior, and the database needs to be configured to meet that specificity. A poorly configured database can lead to:

Slow queries: Delays that annoy users and cause a loss of revenue.
Excessive resource consumption: Using more CPU and RAM than necessary, making the operation more expensive.
Disk congestion: Increasing latency and the risk of unavailability.
Deadlocks and concurrency issues: Freezing the system and requiring emergency interventions.

PostgreSQL optimization is not a luxury, it’s a necessity. And the points below are just the beginning.

1. Fine-Tuning Configuration Parameters (postgresql.conf)

The postgresql.conf file is the heart of your database. Good PostgreSQL fine-tuning starts here. However, it’s a minefield for those without experience. Changing a parameter incorrectly can cause more problems than solutions.

shared_buffers: Defines the amount of RAM that PostgreSQL will use for data caching. If it’s too low, the system will make constant disk reads, causing slowness. If it’s too high, it can lead to swap issues with the operating system. HTI Tecnologia analyzes the load profile and infrastructure to find the ideal value.
work_mem: Used for operations like ORDER BY and JOIN. If it’s too small, PostgreSQL will have to use temporary files on disk, which is extremely slow. Increasing it can consume too much memory.
maintenance_work_mem: Essential for maintenance operations like VACUUM and CREATE INDEX. A generous value can speed up these critical tasks.
effective_cache_size: Informs PostgreSQL about the size of the cache available at the operating system level, helping the query planner make smarter decisions about using indexes.

# postgresql.conf
# Estimate of the total cache size available to the database,
# including the OS cache. Usually 50-75% of total RAM.
effective_cache_size = 8GB

Adjusting these parameters requires more than a “guess”. The expertise in PostgreSQL optimization from HTI Tecnologia ensures the configuration is perfect for your environment.

2. The Hidden Power of Indexes (And Why They Can Fail)

Indexes are the key to speed. Without them, the database performs a full table scan, a process that becomes unfeasible as data grows. But simply creating indexes randomly isn’t enough.

Usage analysis: Just creating indexes doesn’t solve it. You need to analyze which indexes are actually used and which are wasted. Unused indexes take up disk space and harm write performance (INSERT, UPDATE, DELETE).

SELECT
    relname AS table_name,
    indexrelname AS index_name,
    idx_scan,  
    idx_tup_read, 
    idx_tup_fetch 
FROM
    pg_stat_user_indexes
WHERE
    schemaname = 'public' 
ORDER BY
    idx_scan DESC;

Index Types: Do you know when to use a B-Tree, a GIN, or a BRIN? Each type is optimized for a different scenario. The wrong choice can be as bad as having no index at all.

-- Assume a 'pedidos' table with a 'data_pedido' column
CREATE INDEX idx_pedidos_data_pedido ON pedidos (data_pedido);

-- Assume a 'produtos' table with a 'detalhes' column of type JSONB
CREATE INDEX idx_produtos_detalhes_gin ON produtos USING GIN (detalhes);

REINDEX vs. DROP/CREATE: Maintaining index health is crucial. Periodically, it may be necessary to recreate them to optimize their storage and performance.

HTI Tecnologia uses advanced monitoring tools to identify slow queries and intelligently suggest the creation and optimization of indexes, avoiding a “trial and error” approach.

3. The VACUUM Dilemma and Data Fragmentation

VACUUM is one of the most critical, yet neglected, points of PostgreSQL. When you delete or update a row, it’s not physically removed. Instead, it’s marked as “dead”. VACUUM is the process that “cleans up” these dead rows, freeing up space and preventing “Data Fragmentation”.

autovacuum: autovacuum is an essential tool, but its parameters need PostgreSQL fine-tuning. If it’s too aggressive, it can consume resources unnecessarily. If it’s too slow, it can lead to “table bloat” and, in extreme scenarios, a transaction “wraparound,” which can paralyze the database.

autovacuum = on               
log_autovacuum_min_duration = 1s 
autovacuum_max_workers = 3    
autovacuum_vacuum_cost_delay = 10ms 
autovacuum_vacuum_scale_factor = 0.2 
autovacuum_analyze_scale_factor = 0.1

VACUUM FULL: Be careful with this command! It’s useful for recovering disk space, but it requires an exclusive lock on the table, making it unavailable for use. It’s an operation that requires planning and expertise to be executed during appropriate maintenance windows.

VACUUM FULL public.minha_tabela;

Outsourcing DBA services to HTI Tecnologia means you have experts monitoring and managing autovacuum and cleanup processes 24/7, ensuring your database is always “lean” and with high performance. Learn more about how HTI’s database support can protect your business.

4. SQL Query Optimization (Query Tuning)

The biggest impact on performance often comes from poorly written queries. PostgreSQL’s Query Planner does an incredible job, but if the query is complex, it can get lost.

Using EXPLAIN ANALYZE: This tool is the “X-ray” of your query. It shows the path PostgreSQL took to execute the query, revealing bottlenecks and PostgreSQL optimization opportunities.

EXPLAIN ANALYZE
SELECT
    p.nome_produto,
    c.nome_cliente,
    ped.data_pedido,
    ped.valor_total
FROM
    pedidos ped
JOIN
    clientes c ON ped.cliente_id = c.id
JOIN
    produtos p ON ped.produto_id = p.id
WHERE
    ped.data_pedido BETWEEN '2023-01-01' AND '2023-01-31'
ORDER BY
    ped.valor_total DESC
LIMIT 100;

Best practices: Using JOINs efficiently, avoiding SELECT *, and optimizing subqueries. HTI Tecnologia works side-by-side with your development team to improve SQL code and ensure the database is accessed in the most efficient way possible.

SELECT * FROM usuarios WHERE id = 123;
SELECT nome, email, data_cadastro FROM usuarios WHERE id = 123;

5. Table Partitioning for Large Volumes of Data

If you have tables with billions of records, partitioning can be a game-changer. Partitioning a table divides it into smaller, more manageable parts, which speeds up queries and optimizes maintenance. However, it’s an architecture that must be planned carefully, as incorrect implementation can cause more headaches than benefits.

CREATE TABLE vendas (
    id SERIAL,
    data_venda DATE NOT NULL,
    valor DECIMAL(10, 2),
    id_produto INT
) PARTITION BY RANGE (data_venda);

CREATE TABLE vendas_2022_q1 PARTITION OF vendas
    FOR VALUES FROM ('2022-01-01') TO ('2022-04-01');

CREATE TABLE vendas_2022_q2 PARTITION OF vendas
    FOR VALUES FROM ('2022-04-01') TO ('2022-07-01');

CREATE TABLE vendas_2022_q3 PARTITION OF vendas
    FOR VALUES FROM ('2022-07-01') TO ('2022-10-01');

CREATE TABLE vendas_2022_q4 PARTITION OF vendas
    FOR VALUES FROM ('2022-10-01') TO ('2023-01-01');

INSERT INTO vendas (data_venda, valor, id_produto) VALUES ('2022-02-15', 150.75, 101);
INSERT INTO vendas (data_venda, valor, id_produto) VALUES ('2022-05-20', 230.00, 105);

6. Log and Monitoring Configuration (Visibility is the Secret)

“What isn’t monitored, can’t be improved.” This maxim is especially true for databases. Configuring detailed logs (without compromising performance) is the foundation for PostgreSQL fine-tuning.

log_min_duration_statement: Sets the minimum time in milliseconds for a query to be logged. This helps identify “slow” queries that need to be optimized.
Monitoring Tools: Solutions like Zabbix, Prometheus, and Grafana, integrated with the expertise of HTI Tecnologia, provide comprehensive dashboards to visualize the health and performance of your PostgreSQL in real-time, allowing you to proactively identify and solve problems.

log_min_duration_statement = 500ms

7. High Availability and Disaster Recovery

Performance means nothing if your database isn’t available. A complete PostgreSQL fine-tuning includes the architecture to ensure operational continuity.

Replication: Replication solutions, such as physical replication (streaming replication) and logical replication, are crucial for having a fallback database in case of failure.
Backup and Restore: Having a robust backup policy and regularly testing the restoration process is the only guarantee against data loss.

wal_level = replica       
max_wal_senders = 10      
wal_keep_size = 512MB     
archive_mode = on         
archive_command = 'cp %p /path/to/wal_archive/%f' 
TYPE  DATABASE        USER            ADDRESS                 METHOD
host    replication     all             192.168.1.0/24          scram-sha-256

TYPE  DATABASE        USER            ADDRESS                 METHOD
host    replication     all             192.168.1.0/24          scram-sha-256

# On the Standby server
pg_basebackup -h <PRIMARY_IP> -p 5432 -U replicator -D /var/lib/postgresql/data -Fp -Xs -R

HTI Tecnologia not only optimizes your database but also implements and manages the high-availability architecture, ensuring your operation never stops. Read more about how HTI Tecnologia guarantees high availability for your company.

Why Outsource PostgreSQL Fine-Tuning to HTI Tecnologia?

HTI Tecnologia stands out in the market because it goes beyond simple consulting. Our team of SQL and NoSQL database specialists has years of experience in PostgreSQL optimization for large companies. We are not just a service; we are an extension of your team, acting proactively to prevent problems before they happen.

Technical Focus: While your internal team focuses on the core business, we specialize in databases. It’s our sole and total dedication.
Risk Reduction: Performance and security issues are mitigated with our 24/7 monitoring and specialized support.
Operational Continuity: With our service, your company has the guarantee of a database that is always available and high-performing.

Don’t waste any more time and resources on performance problems that could be solved by specialists. Let HTI Tecnologia handle the complexity of PostgreSQL fine-tuning for you.

Are you ready to take your database performance to the next level?

Speak with one of our PostgreSQL specialists right now. Schedule a no-obligation meeting and discover how HTI Tecnologia can transform your business performance.

Schedule a meeting here