Best Hosting for Side Projects

How we picked

Selecting the best hosting for side projects requires looking past marketing claims and evaluating concrete limits, quotas, and billing models. We evaluated four providers against the metrics that actually matter when you are building and shipping on your own dime: free tier generosity, pricing predictability, resource ceilings, and ease of deployment. Side projects live or die by whether they can sit quietly in the background without costing money when idle, and whether they punish you with surprise bills if a post hits Hacker News.

We ignored enterprise add-ons, sales-contact tiers, and vanity features. We focused strictly on what you get at the entry level, how the platform handles traffic growth, and whether a sudden spike will break your budget or just your app.

The shortlist

Each of these four platforms solves side project hosting differently, appealing to distinct developer workflows and technical stacks.

Vercel

Vercel is the managed platform built by the team behind Next.js, priced on edge requests and data transfer with a usable free tier. The free Hobby plan includes 1M edge requests and 100 GB data transfer per month at no cost, making it an exceptional home for frontend applications and static sites. Zero-config deployment for Next.js is standard since the same team builds both frameworks and infrastructure, and preview deployments per branch are included rather than held back as an upsell.

The primary trade-off is how Vercel handles scaling. Usage-based overages mean a traffic spike produces a bill rather than a hard cap, and the Pro plan costs $20/mo with 10M edge requests per month, then charges from $2 per additional 1M, along with 1 TB of transfer then from $0.15 per GB. Furthermore, the Hobby plan is strictly limited to a single developer seat. If you want to compare similar frontend-focused architectures, look at Vercel vs Netlify: Which Should You Deploy On?.

Netlify

Netlify is a Jamstack host that moved to a single credit-based currency covering builds, bandwidth, and compute. Its pricing structure features a Free plan with 300 credits, a Personal plan at $9/mo for 1,000 credits, a Pro plan at $20/mo for 3,000 credits with unlimited members, and an Enterprise tier with custom pricing. Credits are consumed dynamically by deployments, compute, bandwidth, and requests.

Netlify shines by offering a $9 Personal tier that sits comfortably between free options and expensive team plans, filling a gap that Vercel leaves open. Pro also allows unlimited team members at $20/mo rather than forcing per-seat charges. However, using a unified credit pool makes it hard to predict what your actual traffic will cost until you run it in production, and the free plan's 300 credits is a much smaller allowance than Vercel's generous request pool.

Railway

Railway is a deploy-from-git platform where the subscription is a usage credit, not a feature tier, meaning you pay for what your containers actually consume. It offers a Free Trial with a one-time $5 credit valid for 30 days and a 2 vCPU / 0.5 GB service cap; a Free plan with $1/month of credit and a 1 vCPU / 0.5 GB per-service cap; a Hobby plan at $5/mo which includes $5/month of credit and raises the per-service ceiling to 48 vCPU and 48 GB; and a Pro plan at $20/mo which includes $20/month of credit and raises the per-service ceiling to 1,000 vCPU and 1 TB.

The big win with Railway is that the subscription fee is credit, so a low-traffic app on Hobby effectively costs $5 total with no hidden platform fees. You can deploy directly from a git repository with zero container or infrastructure configuration. The downsides are that usage above the included credit is billed on top, the free plan's $1/month credit and 0.5 GB limit is too tight for most real applications, and forecasting your bill requires predicting container resource consumption rather than just simple request volumes.

DigitalOcean

DigitalOcean is a developer-focused cloud offering predictable flat-rate Linux VMs known as Droplets, backed by generous bandwidth allocations. Basic Droplets start at $4/mo for 1 vCPU, 512 MiB RAM, 10 GiB SSD, and 500 GiB transfer, while the $6/mo tier steps you up to 1 vCPU, 1 GiB RAM, 25 GiB SSD, and 1,000 GiB transfer. They are billed hourly with a monthly cap, so a destroyed Droplet stops costing money immediately.

For traditional full-stack side projects running Docker, Python, Go, or Ruby, DigitalOcean provides flat monthly pricing where bandwidth is included, keeping bills entirely predictable. The $4 and $6 entry points are cheap enough for side projects to run indefinitely. The catch is that 512 MiB RAM is too small for most modern Node or Docker workloads, making $6 the realistic floor, and shared-CPU Basic tiers will throttle under sustained CPU loads. Most importantly, you manage the server entirely yourself: OS patching, backups, and monitoring are completely on you.

What to watch out for

Side project hosting traps developers through hidden overages, resource starvation, and unexpected operational overhead. When you are picking a host, you need to understand how the billing engine reacts to success and what happens when your code consumes more resources than anticipated.

Usage-based billing versus flat-rate predictability is the single biggest trap. Platforms like Vercel and Railway bill you dynamically for consumption past your initial tier or credits. If your side project gets linked on a major aggregator site, a usage-based host will scale your infrastructure and hand you an unexpected bill at the end of the month. Conversely, flat-rate providers like DigitalOcean cap your server resources entirely; when you hit the CPU or RAM limit, your app slows down or crashes rather than generating a surprise invoice, but you take on the burden of sysadmin work like setting up firewalls and configuring security patches.

Resource floors also catch developers off guard, particularly on free or cheap tiers. A container limit of 0.5 GB RAM on Railway's free plan or a 512 MiB Droplet on DigitalOcean will crash instantly if you try to run memory-heavy build tools, modern JavaScript runtimes, or unoptimized database queries alongside your application. Always verify the memory and CPU limits per service, not just the monthly dollar price, to ensure your stack can actually boot before worrying about how it handles traffic.