Check if value exists in Postgres array

I Spy, with my little '!= ALL'

Assuring that a value does not exist in the array is cinch with the != ALL syntax:

SELECT * FROM table WHERE 'the_ex' != ALL(array_column);
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This query will isolate rows where 'the_ex' has left no trace within the array. Trust me, it's better this way.

Overlapping arrays: Cross-checker '&&'

The array overlap operator && steps up when you yearn to validate shared elements between two arrays:

SELECT * FROM table WHERE array_column && ARRAY['may_be_here', 'or_here']::text[];
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Only rows are divulged where array_column shares common secrets with our inquisitive array of potential elements.

'@>' and ARRAY: subset sleuths

Take a long hard look at the @> operator and ARRAY constructor when your objective is to detect if an array nurses a subset:

SELECT * FROM table WHERE array_column @> ARRAY['missing_diamond']::text[];
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This promptly nabs rows housing the 'missing_diamond' treasure in the array_column.

Array uncoiling with unnest and IN

Circumstances demand detailed scrutiny and individual inspection of each value in the array:

SELECT * FROM table, unnest(array_column) AS element WHERE element = 'jackpot';
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Each value is examined under the elementry magnifying glass as distinct rows from array_column.

B-tree index: Turbocharging 'ANY' queries

Consistent use of the ANY construct calls for a B-tree index to ramp up your queries:

CREATE INDEX idx_array_column ON table USING btree (array_column);
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The above ritual will boost performance for and ANY search parties.

Souped-up Searches with GIN or GiST

Got larger arrays or intricate lookups? Use GIN or GiST indexes for those operations:

CREATE INDEX idx_array_gin ON table USING gin (array_column);
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These indexes fuel array operators to race past performance blues.

NULL handling: The invisible passenger

Beware of NULL values while checking array contents, as they play hide and seek.

Subquery spelunking with ANY

For demanding scenarios, subqueries can be paired with ANY to craft intricate checks.

Caution: '!= ANY()' decoy

Avoid the siren song of using != ANY() erroneously when purging array of a value.

JSON array maneuvers

Use array functions to navigate JSON arrays for quick access to elements.

Replacing 'ilike' with '@>'

In select patterns, swap ilike with @> to trim your array search quests.

Practices for professional programmers

DISTINCT: Dodging duplicates

When duplicate values sneak into your array, insist on unique hits with DISTINCT:

SELECT DISTINCT * FROM table WHERE 'unique_unicorn' = ANY(array_column);
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Multidimensional arrays: It's more complicated

Mind the dimension or flatten arrays while dealing with multi-tiered arrays.

JSON arrays: The right tool for the job

While mining JSON array elements, use jsonb_array_elements_text and IN for a more focused search:

SELECT * FROM table, jsonb_array_elements_text(json_column) WHERE value = 'hidden_treasure';
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Paramount, the security

Injecting user input into array lookups? Safeguard with prepared statements or query parameters for SQL injection.