Best Instagram Post Scrapers 2026 [No-Code + API Edition]

⚡ 30-Second Summary

1. I tested five Instagram post scrapers across data quality, pricing, usability, scalability, and speed

2. lobstr.io is the best Instagram post scraper overall. It gives the strongest balance of no-code setup, API access, clean exports, built-in scheduling, bulk input, and affordable scale pricing

3. Apify is the best second choice. It gives richer detailed data, especially for comments, video, music, mentions, and tagged users. Pick it for deeper post analysis. The trade-off: detailed runs are slower, and at scale Apify is more than 3x more expensive than lobstr.io

4. SociaVault is the fastest API. It hit 196.4 posts per minute in the test and stays affordable. Pick it if you are a developer who can handle pagination, cleanup, scheduling, and JSON-only output yourself

5. ScrapeCreators has the most predictable pricing. It has the lowest guaranteed cost per 1,000 results. Scrapfly looks cheaper on paper, but its price is variable, it can jump to $0.33/1K when residential proxy kicks in. ScrapeCreators is slower and returns the same raw, noisy output as SociaVault, but the price never surprises you

6. ScrapFly gives developers the most control. It is Python-first and flexible, but it was the slowest tool in the test and needs more technical setup. Good for builders, not for people who want a button

7. Bright Data didn't make the main comparison. Its profile discovery endpoint ignores result limits, I asked for 45 posts and it returned 6,648 with the job still running. It works for URL-first workflows, but not for profile-first scraping

Instagram post scraping looks simple until you try to make it repeatable.

One profile URL. A few recent posts. Captions, hashtags, likes, comments, maybe video data.

Then the problems start: login walls, broken selectors, missing fields, and pagination that behaves like it has plans of its own.

So I tested five Instagram post scrapers against the same profile.

I compared them on data quality, pricing, usability, scalability, and speed.

The goal was simple: find which tools can reliably turn an Instagram account into usable post data, without needing constant hand-holding.

Quick Comparison

⚠️ Scrapfly's cost range reflects datacenter-only (low end) vs full residential proxy (high end). The switch is automatic; you cannot predict or cap it per run.

Score summary

Each criterion scored /5 based on measured test data. Overall = unweighted average across 6 criteria.

How each criterion was scored

1. Data: reliably populated field count, comment inclusion, exclusive fields, schema cleanliness
2. Cost: scale $/1K + pricing predictability + free tier
3. Speed: posts per minute, rank order (measured)
4. Scalability: monthly ceiling + built-in concurrency + bulk input + scheduling
5. Usability: no-code UI, input format breadth, filtering, exports, programmatic access
6. Support: available channels + response time evidence + review sentiment

Just tell me which Instagram post scraper to use

Is it legal to scrape Instagram Posts?

Yes, it's legal under certain conditions.

That does not automatically make scraping illegal.

The bigger legal risk is usually how the data is used.

Storing, republishing, reselling, or combining scraped data with personal information can create copyright, privacy, contract, or data-protection issues.

How to stay on the right side:

1. Collect data internally — research, analysis, model training
2. Don't republish Instagram Posts content on a public-facing surface
3. Don't combine with PII for profiling without a legal basis
4. Respect rate limits — don't hammer the platform

Here's how I evaluated the scrapers.

How I chose the best Instagram Post scrapers

I started with Reddit threads, developer forums, and community discussions to identify the problems users repeatedly complained about.

Based on that, I narrowed the criteria to 5 pain points.

1. Data
2. Cost
3. Usability
4. Scalability
5. Speed

Data

For data quality, I looked at what each scraper actually returned, not just how many fields appeared in the output.

A high field count is not always better. Some fields are useful, some are always empty, and some look like Instagram internal clutter that nobody asked for.

I focused on:

1. How many fields were reliably populated
2. Which fields were null
3. Whether comments were included
4. Whether author and engagement data were available

Cost

I normalized pricing to cost per 1,000 results at both entry-level and scale pricing.

Usability

I evaluated usability through input support, filtering, and ease of use.

1. Input support covered profile URLs, usernames, individual post URLs, and reel URLs
2. Filters covered date filtering, result limits, and post type
3. Ease of use covered the full workflow, from setup and job execution to export formats and integrations

Scalability

I estimated how many rows each scraper could collect in 30 days if it ran continuously.

I multiplied each tool's measured rows per minute by the total minutes in a 30-day month.

Where concurrency was available, I treated it as a separate multiplier.

Speed

I used the same benchmark with full data collection enabled.

I measured the total time needed to return the maximum available results, then normalized it to minutes per 1,000 results.

Bonus: Customer support

I also checked customer support: what channels exist, and what real users say about them in reviews.

When a scrape breaks mid-run, response time matters as much as the fix.

Next, I built a longlist of tools from Google searches, and AI recommendations.

What I left out and why

1. Tools that require an Instagram login... Chrome extensions, private API libraries like instagrapi. They work until Instagram flags the session, and then it's your account that pays for it
2. Abandoned GitHub repos... drawrowfly, postaddictme, and a dozen others. Instagram rotates its internals every few weeks and these haven't seen a commit in years
3. Marketplace listings... the RapidAPI wrappers built by solo developers. No SLA, no company behind them, and half the listings are reselling the same broken endpoint under a different name
4. Low-use Apify actors. There are dozens of community-built Instagram actors on Apify. I only tested the most-used Instagram Post Scraper, built and maintained by Apify itself.

Five tools made the cut. Here they are.

The best Instagram Post scrapers

⚠️ Scrapfly's cost range reflects datacenter-only (low end) vs full residential proxy (high end). The switch is automatic; you cannot predict or cap it per run.

1. lobstr.io

Data

Richness

61 curated fields in lobstr.io's own snake_case schema, not a raw Instagram API pass-through. 54 fields are reliably populated; 7 are always null.

Fields (61 total)

Exclusive

Freshness

I tested freshness by running all five tools against @9gag at the same time and checking whether they returned the newest post.

lobstr.io returned the latest post, but this was not a differentiator: all five tools returned the same newest post in this test.

So freshness was basically a tie.

Data score: 4/5 — 54 reliable fields, 15 embedded comment texts; 7 always-null fields cap it

Cost

lobstr.io uses a credit-based monthly subscription.

1. FREE plan: 100 credits/month
2. STARTER plan: $2.00 per 1,000 results
3. TEAM plan: $0.50 per 1,000 results

The pricing is simple and predictable, with a much lower cost at higher volume on the Team plan.

Cost score: 3/5 — $0.50/1K at scale, predictable subscription, free tier available

Usability

lobstr.io keeps the workflow no-code and fairly direct. You add Instagram targets, adjust the settings, and export the results.

Ways to feed it a job

1. A username, like 9gag
2. A full Instagram profile URL
3. Post/Reel URLs with a CSV or TXT file for bulk input

It accepts both usernames and full profile URLs, then normalizes them internally. That keeps the setup simple, especially if your input list is not perfectly tidy.

Pre-scrape settings

The controls are practical, not overbuilt:

1. Relative or absolute date filters
2. Skip pinned posts
3. Maximum unique results
4. Maximum results per task
5. Number of processing slots
6. Unique results only
7. Remove line breaks

The skip pinned posts toggle is a nice touch. Instagram profiles often keep older pinned posts at the top, and excluding them saves you from cleaning them out later.

The scheduling flow supports minutes, hours, days, weeks, and months, with timezone control. That makes it practical for monitoring Instagram profiles over time, not just pulling a one-off dataset.

Standout features

1. Live results while the run is still in progress
2. Daily credit cap with auto-pause
3. Stop runs anytime
4. Built-in deduplication
5. Bulk input via file upload
6. Webhook and email alerts
7. Exports to CSV, JSON, Excel, Sheets, S3, SFTP, or email
8. API, Python SDK, CLI, and MCP support

Usability score: 5/5 — no-code UI, all input formats, filtering, multiple export formats, API/SDK/CLI/MCP

Scalability

At 69.2 posts/min, one Slot can pull roughly ~3M posts/month if it runs 24/7.

That is before parallelization. lobstr.io lets you add up to 20 Slots per Squid, with each Slot running as a separate bot.

In practice, that means throughput can scale close to linearly.

Scalability score: 5/5 — 3M ceiling + built-in concurrency + bulk input + scheduling

Speed

lobstr.io scraped 45 posts from @9gag in 39 seconds.

That works out to about 69.2 posts per minute, or 14.44 minutes per 1,000 results.

The speed is solid for small and mid-sized profile scraping jobs. It is not the fastest in this test, but it is quick enough without making the workflow feel slow.

Speed score: 4/5 — 69.2 posts/min, second fastest tested

Customer support

lobstr.io offers support through a live chat widget directly on the website, plus email support.

This is also one of the few themes that shows up repeatedly in Capterra reviews. Not the usual "great support" confetti, either.

Users specifically mention fast replies, friendly help, and a team that seems to know the product rather than just forwarding your issue into the void.

Support score: 5/5 — live chat + consistently positive Capterra reviews

Best for: Teams that want a balanced scraper with no-code setup, clean exports, and predictable pricing. Speed is solid, and scalability improves with Slots, especially if you want growth without building the whole workflow yourself.

2. Apify

Scores and data below use detailedData (the recommended tier for most use cases). basicData scores are shown where they differ.

Data

Richness

Two tiers on the same actor. basicData: 19 top-level fields, 17 reliably populated. detailedData: 26 top-level fields, 24 reliably populated, plus nested arrays totaling 79 fields when flattened.

Fields — basicData (19 total)

Fields added by detailedData (7 additional top-level, plus nested arrays)

Exclusive

SociaVault and ScrapeCreators contain raw audio metadata buried in Instagram's internal structure, but none of the other tested tools surface it as a clean named field.

lobstr.io embeds 15 comments per post but text only; no other tool tested returns per-comment author, timestamp, or like count.

Data score: 3/5 — 26 reliable fields (detailed); best video metadata, but half the field count of lobstr.io

Cost

Apify runs on a monthly subscription.

There are two separate result charges: one for the post itself, and another if you collect post details.

1. FREE tier: available, with $5 credit
2. Starter: $2.30 per 1,000 results
3. Business: $1.60 per 1,000 results

Compared with lobstr.io, Apify is only slightly pricier on the Starter plan, but at higher volume it becomes over 3x more expensive for the same Instagram post data.

Cost score: 2/5 — $1.60/1K (detailed) at scale, most expensive tested

Usability

Apify gives you both a no-code Actor form and API access.

The UI is fairly clear: add Instagram targets, set result limits, choose the data detail level, and start the run.

Ways to feed it a job

1. A username or handle, like 9gag
2. A full Instagram profile URL
3. Individual post URLs
4. Reel URLs
5. Multiple targets in one run

Pre-scrape settings

The controls are straightforward:

1. Maximum posts per profile
2. Skip pinned posts
3. Absolute or relative date filter
4. Basic or detailed data

The data detail level setting matters. Basic data is faster and cheaper to process, while detailed data adds fields like latest comments, music info, paid partnership status, and video play count.

Standout features

1. Built-in date filtering with absolute or relative dates
2. Skip pinned posts option
3. Scheduling and webhooks through Apify
4. Export to JSON, CSV, Excel, XML, and JSON Lines
5. API access with Python and JavaScript SDKs
6. MCP server available

Usability score: 4/5 — no-code UI, all input formats, filtering, multiple exports, API/SDK/MCP

Scalability

At 145.1 posts/min, Apify's basicData mode can pull roughly ~6.3M posts/month if it runs 24/7.

With detailedData, throughput drops to 56.3 posts/min, or about ~2.4M posts/month.

In practice, Apify scales well for multi-profile scraping. You can pass multiple handles in one run, and the Actor handles concurrency internally.

The main scaling limit is cost, since higher volume means higher result-based billing.

Scalability score: 4/5 — 2.4M ceiling + concurrency + bulk input + built-in scheduling

Speed

Apify's speed depends on the data mode.

With basicData, it scraped 45 posts from @9gag in 18 seconds. That works out to about 145.1 posts per minute, or 6.89 minutes per 1,000 results.

With detailedData, the same scrape took 48 seconds. That drops to about 56.3 posts per minute, or 17.74 minutes per 1,000 results.

The basic mode is fast, but detailed mode adds a noticeable delay.

Speed score: 3/5 — 56.3 posts/min (detailed), third of five

Customer support

Apify offers support through live chat, tickets, and Discord.

Live chat works for basic questions, while actor-specific troubleshooting is better handled through the issue system.

The catch: this actor showed a 1.9-day issue response time.

That is manageable for non-urgent bugs, but slow when a scraping workflow is already breaking politely in the background.

Support score: 3/5 — live chat + Discord + tickets, but 1.9-day actor issue response time

Best for: Users who want flexible Instagram scraping with deeper data and multi-profile runs, and who are okay paying more as volume grows.

3. SociaVault

Data

Richness

SociaVault gives you 25 useful fields out of 131 total. The remaining fields are Instagram-internal implementation data that passes through in the response but carries no value for most use cases. Eight fields are always null.

Fields (25 useful of 131 total)

Exclusive

Both fields are part of the 25 useful fields — but they require extraction from a 131-field response that includes a lot of noise.

Cost

SociaVault uses prepaid credit packs instead of subscriptions, and unused credits do not expire.

For Instagram post scraping, each page costs 1 credit and returns around 12 posts, so collecting 1,000 posts takes about 84 credits.

1. Free tier: not available
2. Starter pack: $0.40 per 1,000 results
3. Enterprise pack: $0.17 per 1,000 results

SociaVault is affordable for larger scraping jobs.

Cost score: 4/5 — $0.17/1K at scale, affordable and fully predictable; no free tier

Usability

SociaVault is API-only.

The workflow is simple but developer-facing: send a request with an Instagram handle, collect one page of results, then use the cursor to fetch the next page.

Ways to feed it a job

1. A plain Instagram username, like 9gag

That is the only supported input format. Profile URLs, post URLs, and reel URLs are rejected, so you need to strip everything down to the handle before sending the request.

API controls

The controls are minimal:

1. handle — the Instagram username to scrape
2. max_id — pagination cursor for the next page

Standout features

1. Very quick API setup
2. Clear error messages for bad inputs
3. No separate scraper activation needed
4. Simple cursor-based pagination
5. Works well for lightweight developer workflows
6. Simple enough for one-pass LLM implementation from the reference docs

Keep in mind

1. Auth uses X-API-Key in the request header rather than the standard Authorization: Bearer format, easy to miss if you're following a generic REST pattern
2. No bulk input (single-handle), date filter, or skip-pinned-post option
3. No webhooks or built-in scheduling; use an external scheduler (cron, Zapier, n8n) for recurring collection jobs
4. JSON only; no built-in CSV, Excel, or webhook delivery

Usability score: 2/5 — API only, username-only input, no filtering, JSON only, non-standard auth header

Scalability

At 196.4 posts/min, SociaVault can pull roughly ~8.5M posts/month if it runs 24/7.

There is no bulk input, so each request targets one handle at a time.

In practice, scaling means running concurrent requests yourself. The API is fast, but orchestration is on you.

Scalability score: 3/5 — highest raw ceiling (8.5M posts/month), but no built-in concurrency, bulk input, or scheduling

Speed

SociaVault scraped 45 posts from @9gag in 13.7 seconds.

That works out to about 196.4 posts per minute, or 5.09 minutes per 1,000 results.

For an API-only tool, this is very fast. The average page response time was around 3.4 seconds, which makes pagination feel fairly painless.

Speed score: 5/5 — 196.4 posts/min, fastest tested by a wide margin

Customer support

SociaVault's support is email-based, which already puts it a step behind tools with live chat or tickets.

Clicking the support option opens your default mail app, so there is no in-app thread, visible queue, or quick escalation path.

For a fast API, the support experience feels oddly slow.

Support score: 2/5 — email only, clicking support opens default mail app

Best for: Developers who want a fast, affordable API and do not mind handling pagination, cleanup, and scheduling themselves. It can scale well, but you have to build the workflow around it.

4. ScrapeCreators

Data

Richness

Fields (24 useful of 131 total)

Exclusive

No unique exclusive fields.

Cost

ScrapeCreators uses a credit-based model with one-time packs. Credits never expire, so there's no monthly reset quietly eating your balance.

For Instagram post scraping, each page costs 1 credit and returns around 12 posts, so collecting 1,000 results takes about 84 credits.

1. Free tier: available
2. Freelance: about $0.16 per 1,000 results
3. Business: about $0.08 per 1,000 results

ScrapeCreators has the most predictable pricing of any tool tested. Scrapfly's advertised rate looks cheaper, but its residential proxy auto-switch can push the real cost to $0.33/1K or more. ScrapeCreators' rate is fixed: one-time credit packs, no proxy surprises.

Cost score: 5/5 — $0.08/1K at scale, lowest guaranteed cost, fully predictable, free tier available

Usability

ScrapeCreators is a REST API, so there is no visual setup flow here.

You send an Instagram handle, get one page of posts back, then keep going with the next-page cursor.

Ways to feed it a job

1. A plain Instagram username, like 9gag

ScrapeCreators keeps input strict. It does not accept profile links, post links, or reel links, so URLs need to be converted into handles first.

API controls

The setup is lean:

1. handle — the Instagram account to scrape
2. next_max_id — cursor for loading the next page

Standout features

1. Uses a standard x-api-key header
2. Simple pagination model
3. Good fit for small API-based workflows
4. Easy for LLMs to implement from the docs

Keep in mind

There is no bulk input (single-handle), date filter, built-in scheduling, or skip-pinned-post control.

1. JSON only; no built-in CSV, Excel, or webhook delivery

Usability score: 2/5 — API only, username-only input, no filtering, JSON only

Scalability

At 41.5 posts/min, ScrapeCreators can pull roughly ~1.8M posts/month if it runs 24/7.

There is no bulk input, so each request handles one Instagram account at a time.

In practice, you can scale ScrapeCreators with concurrent requests, but page speeds vary a lot, so monthly throughput is harder to predict.

Scalability score: 2/5 — 1.8M ceiling, no built-in concurrency, bulk input, or scheduling

Speed

ScrapeCreators scraped 45 posts from @9gag in 65.1 seconds.

That works out to about 41.5 posts per minute, or 24.12 minutes per 1,000 results.

The main issue is consistency. Page response times ranged from 8.7 seconds to 27.9 seconds, so the scrape works, but it does not move at a steady pace.

Speed score: 2/5 — 41.5 posts/min, fourth of five; response times ranged 8.7s to 27.9s

Customer support

ScrapeCreators also relies on email support, with the address shown directly inside the dashboard.

It is easy to find, but still fairly barebones: no live chat, no ticket status, no visible response time.

For a developer API, that may be acceptable. For urgent scraping issues, it feels like sending a message into the inbox cave.

Support score: 2/5 — email only, shown in dashboard; no ticket status or response time commitment

Best for: Cost-conscious developers who want a guaranteed per-result price with no proxy-related surprises, and can tolerate slower, less predictable response times.

5. Scrapfly

Data

Richness

16 fields — a JMESPath-filtered selection from Instagram's raw GraphQL response. Cleanest output of any API tool tested: no noise fields, no internal Instagram implementation details, consistent naming. 12 of 16 are reliably populated; 4 are always null for the profile feed endpoint.

Fields (16 total)

Exclusive

No exclusive fields. The 16-field output is a JMESPath-filtered subset of the raw Instagram GraphQL response — cleaner naming than SociaVault and ScrapeCreators, but no field is uniquely available here that isn't in other tools' outputs.

Data score: 2/5 — 16 clean fields, cleanest schema tested, but fewest useful fields and no comment text

Cost

Scrapfly uses a monthly subscription and pay-as-you-go model.

Each scrape call consumes credits, but the cost depends on the proxy type: datacenter calls are cheap, while residential calls cost much more.

For this Instagram post test, scraping 45 posts took 28 API credits: 3 datacenter calls and 1 residential call.

That works out to roughly 622 credits per 1,000 results, though the real cost can move around depending on proxy use.

1. Free tier: not available
2. Discovery: about $0.09 per 1,000 results
3. Enterprise: about $0.06 per 1,000 results

That estimate looks low, but it depends heavily on proxy use.

If all pages hit residential proxy mode, the cost can jump to around $0.33 per 1,000 results on the Discovery plan, more than 3x the test-based estimate. At the Enterprise plan rate, the same residential scenario works out to around $0.20 per 1,000 results.

The fun part: the residential switch is automatic, which makes it unpredictable.

Cost score: 2/5 — $0.09–$0.33/1K, automatic residential proxy switch can jump cost 3.5× mid-run

Usability

Scrapfly is the most developer-heavy option here. This is not a no-code tool or a simple REST API for Instagram posts.

You run Scrapfly's open-source Python scraper in your own environment, with Scrapfly handling the proxy infrastructure behind it.

Ways to feed it a job

1. A plain Instagram username, passed as the account argument

Scraper controls

The main controls are:

1. max_pages — limits how many pages to scrape
2. asp — enables Scrapfly's anti-bot bypass
3. SCRAPFLY_KEY — API key set as an environment variable

Standout features

1. Built-in anti-bot bypass
2. Open-source scraper code
3. Python async support
4. Automatic pagination
5. Scraper logic can be modified
6. Useful for developers who want control over the scraping code

Keep in mind

1. Scrapfly is not beginner-friendly
2. You need Python, async code, environment variables, and the GitHub scraper setup before you get results
3. There is also no built-in scheduling, webhook flow, or skip-pinned-post option
4. No built-in bulk input parameter — multi-handle scraping is possible via asyncio.gather(), but the orchestration is on you
5. The proxy switching is automatic, so usage can jump without much warning
6. No built-in export — output is Python dicts; writing to JSON, CSV, or a database requires your own code

Usability score: 1/5 — Python async required, no REST option, no no-code UI, manual export only

Scalability

At 16.6 posts/min, Scrapfly can pull roughly ~716K posts/month if it runs 24/7.

In practice, Scrapfly can scale if you are comfortable managing async Python.

The trade-off is speed: the anti-bot setup gives you more reliability, but it does not exactly sprint.

Scalability score: 2/5 — 716K ceiling, lowest tested; async concurrency possible but fully DIY

Speed

Scrapfly scraped 45 posts from @9gag in 162.7 seconds.

That works out to about 16.6 posts per minute, or 60.26 minutes per 1,000 results.

Scrapfly is slow in this test, especially compared with the simpler API tools. The anti-bot setup may help with reliability, but speed is clearly the trade-off here.

Speed score: 1/5 — 16.6 posts/min, slowest tested by a wide margin

Customer support

ScrapFly's GitHub support runs through Issues, which is transparent but not especially reassuring here.

There were 0 open issues and 29 closed issues, so it does not look neglected.

Still, this is GitHub-style support: useful for technical bugs, less useful if you need fast help during a live scraping problem.

Support score: 2/5 — GitHub Issues only, 0 open / 29 closed; no live chat, tickets, or email

Best for: Python developers who value control and anti-bot infrastructure over speed. It can scale with async code, but it is slower and cost can rise when residential proxy mode kicks in.

The scraper that didn't make the list

Bright Data

Bright Data has genuinely good data: 41 clean fields, author follower counts per post, and rich comment objects with commenter avatars.

On paper, it looks competitive. In practice, one issue disqualified it from this comparison.

Every tool in this article follows the same basic workflow: give it an Instagram account, get the last N posts back.

Bright Data could not do that cleanly.

Its post discovery mode ignored the result limit. I asked for 45 posts; it returned 6,648 and was still running.

Its collect-by-URL mode worked fast and cleanly, but only if I supplied the post URLs upfront.

That makes Bright Data useful for enriching known post URLs, but not for profile-to-post scraping.

FAQ

Do these scrapers require logging into Instagram?

No. All five tools scrape public Instagram profiles without any authentication.

None of them require an Instagram account or session cookie.

Can I scrape Instagram posts without writing code?

lobstr.io and Apify both have no-code UIs.

lobstr.io is the simpler setup: add a profile URL, set a limit, run.

Apify requires more familiarity with the Actor model but is fully no-code once configured.

Do these tools work on private Instagram accounts?

No. All tested tools scrape public profiles only.

Private accounts are not accessible without authentication, which none of these tools support.

Can I scrape posts from multiple accounts in one run?

lobstr.io and Apify support this natively — lobstr.io via multiple tasks, Apify via array input.

SociaVault, ScrapeCreators, and Scrapfly handle one account per request.

You can loop through accounts, but the orchestration is on you.

How fresh is the data?

I ran all five tools against the same profile at the same time and compared the most recent post returned.

Every tool returned the same post. Freshness was not a differentiator — all tools pull live data.

What is the best Instagram post scraper overall?

lobstr.io is the best overall Instagram post scraper in this test.

It does not win every isolated metric. SociaVault is faster. ScrapeCreators is cheaper. Apify returns richer detailed metadata for comments, video, music, and tagged users.

But lobstr.io is the strongest all-rounder because it combines no-code setup, API access, clean exports, built-in scheduling, bulk input, filtering, webhooks, and predictable pricing at scale.

What is the cheapest Instagram post scraper?

ScrapeCreators has the most predictable pricing — $0.16/1K at entry, $0.08/1K at scale, no surprises.

Scrapfly's advertised rate ($0.09/$0.06) looks cheaper on paper, but its anti-bot proxy can switch automatically from datacenter to residential, pushing the real cost to $0.33/1K or higher. In my test, one page switched to residential proxy automatically — if all pages do, the cost reaches $0.33/1K. The price you see on Scrapfly's pricing page is not the price you will reliably pay.

If you want the lowest guaranteed rate, ScrapeCreators wins. The trade-offs: API-only, slower than SociaVault, accepts usernames only, and returns raw 131-field JSON that needs cleanup.

What is the fastest Instagram post scraper?

SociaVault was the fastest Instagram post scraper in this test.

That speed comes with a catch: SociaVault is API-only. You have to handle pagination, cleanup, scheduling, storage, and exports yourself.

For developers, that may be fine. For teams that want a ready-to-run workflow, lobstr.io is slower but much easier to operate repeatedly.

What is the best Instagram post scraper for marketers?

lobstr.io is the best Instagram post scraper for marketers and growth teams.

It supports no-code scraping, profile URLs, usernames, post URLs, reels, bulk uploads, built-in scheduling, and exports to CSV, Excel, Google Sheets, S3, SFTP, and email.

That matters because marketers usually do not want a raw API response. They want usable post data in a format they can analyze, share, or plug into a workflow.

What is the best Instagram post scraper for developers?

SociaVault is the best fit for developers who want speed and a simple API.

It is fast, affordable, and easy to call through REST endpoints. The downside is that it gives you raw JSON and leaves the rest of the workflow to you.

If you want more control over scraping infrastructure, ScrapFly is the more technical Python-based option.

If you want developer access without building the whole pipeline yourself, lobstr.io is the better middle ground because it includes API, SDK, CLI, MCP, webhooks, exports, and scheduling.

What is the best Instagram post scraper for research?

Apify is the best pick if your research depends on richer post metadata.

Its detailedData mode returns stronger structured fields for comments, video, music, mentions, and tagged users.

The trade-off is cost and speed. Detailed mode is slower, and Apify gets more expensive at higher volume.

For research teams that mostly need clean post, caption, hashtag, engagement, owner, carousel, and comment text fields, lobstr.io is the more practical choice.

Conclusion