We have a table containing around 500k rows. The database table is supposed to grow to million of records.

This is how the table looks like:

CREATE TABLE public.influencers
(
    id integer NOT NULL DEFAULT nextval('influencers_id_seq'::regclass),
    location jsonb,
    gender text COLLATE pg_catalog."default",
    birthdate timestamp without time zone,
    ig jsonb,
    contact_info jsonb,
    created_at timestamp without time zone DEFAULT now(),
    updated_at timestamp without time zone DEFAULT now(),
    categories text[] COLLATE pg_catalog."default",
    search_field text COLLATE pg_catalog."default",
    search_vector tsvector,
    ig_updated_at timestamp without time zone,
    CONSTRAINT influencers_pkey PRIMARY KEY (id),
    CONSTRAINT ig_id_must_exist CHECK (ig ? 'id'::text),
    CONSTRAINT ig_username_must_exist CHECK (ig ? 'username'::text)
)

And these are some of the queries we need to perform efficiently:

 SELECT  "public"."influencers".* FROM "public"."influencers" WHERE (ig->'follower_count' IS NOT NULL)  ORDER BY (ig->'follower_count') DESC LIMIT 9 OFFSET 0

SELECT * FROM "public"."influencers" WHERE (ig -> 'follower_count' >= '5000') LIMIT 9 

SELECT SUM(CAST(ig ->> 'follower_count' AS integer)) FROM "public"."influencers" WHERE (ig -> 'follower_count' >= '5000') AND (ig -> 'follower_count' <= '10000') AND (ig->'follower_count' IS NOT NULL)

ig -> follower_count are numeric values.

I read that GIN indexes are mainly intended for searching through composite items (text) so I'm guessing the best index to use would be a BTREE. Would that be correct?

Thanks.

We have a table containing around 500k rows. The database table is supposed to grow to million of records.

This is how the table looks like:

CREATE TABLE public.influencers
(
    id integer NOT NULL DEFAULT nextval('influencers_id_seq'::regclass),
    location jsonb,
    gender text COLLATE pg_catalog."default",
    birthdate timestamp without time zone,
    ig jsonb,
    contact_info jsonb,
    created_at timestamp without time zone DEFAULT now(),
    updated_at timestamp without time zone DEFAULT now(),
    categories text[] COLLATE pg_catalog."default",
    search_field text COLLATE pg_catalog."default",
    search_vector tsvector,
    ig_updated_at timestamp without time zone,
    CONSTRAINT influencers_pkey PRIMARY KEY (id),
    CONSTRAINT ig_id_must_exist CHECK (ig ? 'id'::text),
    CONSTRAINT ig_username_must_exist CHECK (ig ? 'username'::text)
)

And these are some of the queries we need to perform efficiently:

SELECT  "public"."influencers".* 
FROM "public"."influencers" 
WHERE (ig->'follower_count' IS NOT NULL) 
ORDER BY (ig->'follower_count') DESC 
LIMIT 9 
OFFSET 0

SELECT * 
FROM "public"."influencers" 
WHERE (ig->'follower_count' >= '5000') 
LIMIT 9 

SELECT SUM(CAST(ig ->> 'follower_count' AS integer)) 
FROM "public"."influencers" 
WHERE (ig->'follower_count' >= '5000')
  AND (ig->'follower_count' <= '10000')
  AND (ig->'follower_count' IS NOT NULL)

ig -> follower_count are numeric values.

I read that GIN indexes are mainly intended for searching through composite items (text) so I'm guessing the best index to use would be a BTREE. Would that be correct?