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How to Handle Databases with Billions of Records

Dealing with databases containing billions of records demands specific techniques. Here are five key lessons to improve database performance and management.

Forget About JOINs

JOINs can slow down large databases. Use aggregated tables or JSON columns instead.

SELECT data->>'$.field' 
FROM large_table 
WHERE id = 1;
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Be Careful With Indexes

Indexes speed up queries but consume space. Periodically drop unused indexes.

CREATE INDEX idx_name ON table_name (column_name);
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Do Not Rely on Backups

Restoring from backups is slow. Use alternative backup methods like exporting data to text files.

Optimize Your Queries

Write efficient queries and use tools like DbVisualizer's Explore Plan to enhance performance.

EXPLAIN ANALYZE SELECT * 
FROM table_name 
WHERE condition;
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Adopt a Reliable Client

Choose a reliable database client like DbVisualizer for effective management.

FAQs

Why avoid JOINs in large databases?

JOINs can significantly reduce performance. Aggregated tables or JSON columns are better alternatives.

How do indexes impact large databases?

While speeding up queries, indexes also take up disk space. Regularly removing unused indexes helps.

What are alternative backup methods?

Exporting data to text files or using fast import/export tools can speed up recovery.

How to optimize queries?

Use DbVisualizer's Explore Plan to refine and improve query performance.

Conclusion

Handling a billion-record database requires specific strategies. For more comprehensive insights, read the article How To Deal With a Database With Billions of Records.

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