When are indexes a problem?

Every IT professional knows that indexes are the backbone of database performance. They’re like a book’s index: they allow you to find data quickly, preventing the system from having to read every single line in a table. But what happens when the very index, created to be the solution, becomes the bottleneck that chokes your application?

Many infrastructure managers, CTOs, and even experienced DBAs underestimate the invisible cost of a neglected indexing strategy. System performance starts to drop, queries take longer, response time increases, and user experience plummets. It’s an insidious problem, often attributed to other factors, while the root of the issue is silently corrupting your database.

HTI Tecnologia, a specialist in 24/7 database consulting and support, knows that proactive management is the key to stability. In this article, we will delve into the critical signs that your database indexes have become a problem and why the expertise of a specialist might be the only way to rescue the health of your application.

The Silent Problem: How Indexes Become Performance Villains

Query optimization is one of the pillars of a high-performance database. Without adequate indexes, even the simplest query can become a performance nightmare. A SELECT that should take milliseconds turns into a FULL TABLE SCAN of several seconds, consuming resources and generating latency.

However, creating indexes is not an exact science. Too many indexes can be just as harmful as too few. Why? Because with every INSERT, UPDATE, or DELETE, the system needs to not only alter the table but also update all the associated indexes. This creates I/O overhead, increases write time, and, in high-concurrency scenarios, can lead to deadlocks and generalized performance degradation.

The crucial question is: when are indexes a problem? The answer isn’t in a single symptom, but in a combination of factors that point to an outdated and poorly managed indexing strategy.

7 Critical Signs That Your Indexes Are Killing Your Database’s Performance

Is your development team complaining about slow queries? Is your application crashing during peak hours? It’s likely that the problem isn’t the hardware, but rather how your indexes are being used. Recognizing these 7 signs is the first step to solving the problem.

1. Excessive Index Fragmentation

Indexes, especially in relational databases like SQL Server and PostgreSQL, can become fragmented over time. Fragmentation occurs when the logical order of data in the index does not match the physical order on the disk. This forces the system to jump from one block to another to read data, increasing I/O time and, consequently, query time.

Fragmentation is one of the main reasons a system’s performance slowly degrades over months. Without regular reindexing or reorganization maintenance, query latency can increase by up to 50%. A specialist DBA proactively monitors and manages fragmentation, ensuring that data is always organized and accessible.

-- Check fragmentation (for a table)
SELECT avg_fragmentation_in_percent FROM sys.dm_db_index_physical_stats(DB_ID(), OBJECT_ID('YourTable'), NULL, NULL, 'DETAILED');

-- Rebuild an index (for fragmentation > 30%)
ALTER INDEX YourIndex ON YourTable REBUILD;

For PostgreSQL:

-- Check bloat/swelling (requires pg_stat_user_indexes and size analysis)
SELECT relname AS table_name, indexrelname AS index_name, pg_size_pretty(pg_relation_size(indexrelid)) AS index_size
FROM pg_stat_user_indexes WHERE schemaname = 'public' ORDER BY index_size DESC;

-- Rebuild an index (to fix bloat)
REINDEX INDEX YourIndex;

2. Unused Indexes

You created an index a year ago for a specific query, but it was discontinued. What happens to the index? It’s still there, consuming disk space and, more importantly, generating overhead for write operations. “Orphaned” indexes are a silent resource drain, overloading the system’s CPU and I/O without providing any benefit.

SQL Server:

-- List indexes that have never been used for reads (user_seeks, user_scans, user_lookups = 0)
SELECT OBJECT_NAME(s.object_id) AS TableName, i.name AS IndexName, s.user_updates
FROM sys.dm_db_index_usage_stats AS s JOIN sys.indexes AS i ON s.object_id = i.object_id AND s.index_id = i.index_id
WHERE OBJECTPROPERTY(s.object_id, 'IsUserTable') = 1 AND s.database_id = DB_ID()
AND s.user_seeks = 0 AND s.user_scans = 0 AND s.user_lookups = 0 ORDER BY s.user_updates DESC;

-- To remove an index (use with caution!): DROP INDEX YourIndex ON YourTable;

PostgreSQL:

-- List indexes that have never been scanned
SELECT s.relname AS TableName, s.indexrelname AS IndexName, pg_size_pretty(pg_relation_size(s.indexrelid)) AS IndexSize
FROM pg_stat_user_indexes AS s WHERE s.idx_scan = 0 AND s.schemaname = 'public' ORDER BY IndexSize DESC;

-- To remove an index (use with caution!): DROP INDEX YourIndex;

3. Redundant and Duplicate Indexes

It’s surprisingly common to find multiple indexes that serve the same purpose. For example, an index on column (A, B) and another on column (A). The second is, in most cases, redundant, as the first can already be used for queries that filter only by column A. Identifying and removing these indexes is crucial for database health. A senior DBA knows how to identify and optimize these cases, cleaning the database and improving efficiency.

-- List indexes and their columns for manual redundancy analysis
-- SQL Server:
SELECT i.name AS IndexName, COL_NAME(ic.object_id, ic.column_id) AS ColumnName, ic.key_ordinal
FROM sys.indexes AS i JOIN sys.index_columns AS ic ON i.object_id = ic.object_id AND i.index_id = ic.index_id
WHERE i.object_id = OBJECT_ID('YourTable') ORDER BY i.name, ic.key_ordinal;

-- PostgreSQL:
SELECT t.relname AS TableName, i.relname AS IndexName, ARRAY_AGG(a.attname ORDER BY x.indkey) AS IndexedColumns
FROM pg_class t JOIN pg_index ix ON t.oid = ix.indrelid JOIN pg_class i ON i.oid = ix.indexrelid
JOIN pg_attribute a ON a.attrelid = t.oid JOIN UNNEST(ix.indkey) WITH ORDINALITY AS x(attid, ord) ON x.attid = a.attnum
WHERE t.relname = 'your_table' GROUP BY t.relname, i.relname ORDER BY t.relname, i.relname;

4. Constant and Unexpected “Full Table Scans”

Is your query planner ignoring indexes and performing FULL TABLE SCANS? This is a very serious warning sign. It could be due to outdated statistics, poorly defined indexes, or badly written queries that prevent the execution plan optimizer from using the index efficiently. A single FULL TABLE SCAN on a table with millions of rows can paralyze the application for minutes.

SQL Code to Identify and Prevent Full Table Scans:

-- Use EXPLAIN ANALYZE (PostgreSQL) or SHOWPLAN (SQL Server) to see the execution plan.
-- If "Seq Scan" (PostgreSQL) or "Table Scan" (SQL Server) appears on large tables, it's a problem.
EXPLAIN ANALYZE SELECT * FROM YourTable WHERE FilterColumn = 'value';

-- If 'FilterColumn' is not indexed and the table is large, a Seq Scan will be observed.
-- To avoid a Seq Scan (if the column is used in WHERE):
CREATE INDEX idx_yourtable_filtercolumn ON YourTable (FilterColumn);

5. High Write Cost (INSERT/UPDATE/DELETE)

As we already mentioned, each index adds a cost to write operations. If your application has a high volume of INSERTs, UPDATEs, or DELETEs, an excess of indexes can be the cause of latency and prolonged lock times. The ideal is to have a minimum number of indexes for write operations, prioritizing critical queries. The art here is to find the balance between read and write performance.

-- Example: Inserting a record into a table with multiple indexes
INSERT INTO Products (id, name, category_id, price) VALUES (1, 'Keyboard', 10, 150.00);

-- The database will need to write the data to the 'Products' table
-- And also update all existing indexes on the table (e.g., idx_name, idx_category, idx_price)

6. Problems in Aggregation Queries (GROUP BY, ORDER BY)

Many developers forget that indexes aren’t just useful for WHERE clauses. They can also greatly speed up GROUP BY and ORDER BY operations. If these queries are slow, it’s likely that your index structure is not optimized for these operations. A specialized DBA knows how to create composite indexes that satisfy multiple query scenarios, ensuring performance on all fronts.

SQL Code to Optimize GROUP BY/ORDER BY:

-- Aggregation query (can be slow without the correct index)
EXPLAIN ANALYZE
SELECT client_id, COUNT(id) AS TotalOrders, SUM(total_value) AS TotalValues
FROM Orders WHERE order_date >= '2023-01-01' GROUP BY client_id ORDER BY TotalOrders DESC;

-- Composite index that optimizes WHERE and GROUP BY/ORDER BY
CREATE INDEX idx_orders_date_client ON Orders (order_date, client_id);
-- (The order of columns is crucial: `order_date` for the WHERE, `client_id` for GROUP BY)

7. Inappropriate Use of Composite Indexes

Composite indexes are powerful, but their inappropriate use can be a disaster. The order of columns in a composite index is crucial. If you have an index on (state, city) and most of your queries filter only by city, this index may be useless. The query optimizer, in many cases, can only use the leftmost part of the composite index. A database specialist understands the cardinality and selectivity of each column to define the correct order, ensuring the index is as efficient as possible.

SQL Code to Illustrate the Use of Composite Indexes:

-- Example table
CREATE TABLE Users (id INT PRIMARY KEY, state VARCHAR(50), city VARCHAR(50));

-- Composite index (state, city)
CREATE INDEX idx_users_state_city ON Users (state, city);

-- OPTIMIZED Query: Uses the leftmost prefix of the index
EXPLAIN ANALYZE SELECT * FROM Users WHERE state = 'SP' AND city = 'São Paulo';
EXPLAIN ANALYZE SELECT * FROM Users WHERE state = 'SP';

-- NOT OPTIMIZED Query: Does not use the leftmost prefix (state)
EXPLAIN ANALYZE SELECT * FROM Users WHERE city = 'São Paulo';
-- This query will likely do a Full Table Scan, as the index starts with 'state'.

-- If the query by `city` is common, an index on `(city)` or `(city, state)` would be more suitable.

The Hidden Cost of Suboptimal Performance

Database inefficiency is not just a technical problem; it’s a business problem. Slowness leads to user frustration, abandoned shopping carts, revenue loss, and damage to brand reputation. The cost of maintaining an in-house team of DBAs to manage these issues can be prohibitive for many medium and large companies, in addition to the challenge of finding qualified professionals.

This is where outsourcing database management becomes a smart and economically viable strategy. By delegating the management of your databases to a team of specialists, you ensure:

• Technical Focus: Your in-house IT and development team can focus on what they do best: developing and innovating, without worrying about the complexity and routine of database optimization.
• Risk Reduction: The expertise of a team like HTI’s, with decades of experience, mitigates the risk of failures, data loss, and unavailability. Performance management and security are addressed proactively.
• Operational Continuity: With 24/7 support, your company is never left in the lurch. In case of incidents, an elite team of DBAs is ready to act immediately, minimizing downtime and financial impact.

How HTI Tecnologia Can Rescue Your Database’s Performance

HTI Tecnologia acts as an extension of your team, offering specialized consulting, support, and maintenance for various databases, both SQL (MySQL, MariaDB, PostgreSQL, Oracle, SQL Server) and NoSQL (MongoDB, Redis, Neo4J).

Our approach is not limited to fixing problems, but to preventing them. Through continuous and proactive monitoring, our DBAs identify and correct anomalies before they become crises. Index optimization is just one of many areas of action. Our specialists apply market best practices, such as:

• Performance audit: We identify bottlenecks and optimization opportunities, from infrastructure to query optimization.
• Index analysis: We identify redundant, unused indexes, and create new indexing strategies for critical queries.
• Query optimization: We rewrite complex queries to be more efficient and use indexes correctly.
• Fragmentation management: We perform regular maintenance to ensure indexes are always organized and accessible.

HTI’s expertise in high-complexity projects, as shown in our testimonials, allows your company to focus on growth, knowing that the database is in safe hands.

If you are facing performance problems or want to guarantee the availability of your systems 24/7, HTI Tecnologia’s 24/7 Database Maintenance service is the ideal solution.

Don’t Let Poorly Managed Indexes Threaten Your Business

Your database’s performance is not a luxury; it’s a necessity. Ignoring the signs that your database indexes are becoming a problem is a risk your business cannot afford to take.

Don’t wait for the next crisis to act. Ensure your IT infrastructure has the robustness and agility needed to support your company’s growth.

Want to discover how HTI Tecnologia can optimize your database’s performance and ensure 24/7 availability? Schedule a no-obligation meeting with one of our specialists now and learn how we can help your company thrive.

chedule a meeting here

Visit our Blog

Learn more about databases

Learn about monitoring with advanced tools

Have questions about our services? Visit our FAQ

Want to see how we’ve helped other companies? Check out what our clients say in these testimonials!

Discover the History of HTI Tecnologia