Build Buy

The True Cost of Indexing Blockchain Data

Why leading wallets, explorers, and Web3 apps increasingly buy their blockchain data layer instead of building it.

The Build vs Buy Decision

#1

Many teams assume nodes provide the data their app needs. In reality, nodes only provide raw blockchain data. Applications need enriched, indexed, normalized, and modeled data.

Build In-House

Cost $500K-$2M per year

ADVANTAGES

  • Full control and customization

TRADE-OFFS

  • 6-12 months to production
  • $500K-$2M annual cost
  • Constant maintenance

Buy (Moralis)

Cost $3.5K-$54K per year

ADVANTAGES

  • Ship in days, not months
  • 99.9% uptime SLA
  • Production-ready blockchain APIs
  • 5-20x cost savings
  • Zero maintenance overhead

The gap between raw node data and usable application data is where cost and complexity explode.

Let’s compare Token Balances

#2

Full Token Balances
Are Hard

Full token portfolios aren’t stored anywhere onchain, so there’s no single RPC method you can call to fetch them.

To compute token balances reliably, you must:

  1. Identify all token contracts a wallet has ever interacted with
  2. Index all relevant transfer logs (historical + real-time)
  3. Apply deltas to maintain balance state
  4. Resolve decimals, name, symbol, contract verification
  5. Fetch token price & compute USD values
  6. Detect spam / malicious assets
  7. Normalize and format output consistently across chains

Native Token Balances
Are Easy

Native balances are stored on the account itself, so they only require one API call.

eth_getBalance(address)

Edge Cases
That Break
In-House Builds

Many tokens do not update balances through transfer events. They break a core assumption DIY indexers rely on: that token balances always change through transfers.

When this assumption fails, balances require special handling or your data becomes incorrect.

Why It's Difficult Examples
Rebase / staking / yield tokens Balances change without transfers StETH, aTokens, Tokens
LP & liquidity pool tokens Represent baskets of assets, not a single token Uniswap LP tokens, Curve LP
Wrapped & bridged tokens Need canonical asset mapping + price correlation WETH, wstETH, bridged USDC variants
Synthetic & derivative assets Value sourced externally SETH, renBTC, index-backed stablecoins

Scaling Across
Chains = Costs Compound

Every chain has different RPC quirks, indexing rules, metadata sources, and ecosystem standards - so supporting a new chain multiplies work rather than adding it linearly.

How to add a chain internally

Adding more chains dramatically increases complexity.

  1. $1K-$8K/month for each chain RPC node

    Multiplies with redundancy demands

  2. Adapt indexing logic for chain-specific quirks

  3. Token metadata registry upkeep

  4. Test edge cases unique to that chain

  5. Monitor & maintain additional infrastructure

    Breakage surface grows exponentially

  6. Handle chain-specific reorg patterns

TIMELINE

2-4 months

per chain + ongoing maintenance

How to add a new chain on Moralis

Change a single query parameter:

  • No new infrastructure
  • No new code to maintain
  • No operational burden

TIMELINE

Instant

Token Balances are
Just One Endpoint
(We Have 60+)

Every endpoint is its own data pipeline - indexing, enrichment, normalization, pricing, and validation

IF TOKEN BALANCES REQUIRES:

  • Indexing pipelines
  • Metadata registry
  • Pricing feeds
  • Security checks
  • Spam detection

Replicating the entire Moralis Data Layer means building 60+ pipelines.

Example Endpoints What Must Be Built Internally
Wallet API Wallet
  • Balances
  • Portfolio
  • Transfers
  • Approvals
Indexing + spam filters + metadata normalization
Token API Token
  • Metadata
  • Prices
  • Ownership
  • Transfers
Registry + pricing sources + verification
Price APITransactions
  • Full history
  • Function decoding
Archive nodes + trace indexing + ABI resolution
NFT API NFTs
  • Metadata
  • Traits
  • Ownership
  • Transfers
  • Collections
Media caching + rarity computation
DeFi API DeFi
  • Pool state
  • LP Positions
  • Swap Breakdowns
AMM math + real-time pool state sync

  1. If you build one endpoint,
    you've built an integration.


  2. If you build sixty,
    you've built a platform.


  3. Platforms require entire teams.

Cost Comparison

#3

Building your own data pipelines creates fixed, compounding costs; buying with Moralis converts that into predictable, usage-based cost.

Monthly Operating Cost Reality

Monthly Operating Cost Reality
Node only Build internal indexer Moralis Data API
Node hosting $50K-$100K $3K-$15K Included
Indexing
compute + storage
$1K - $15K Included
Engineering headcount $15K - $35K/mo Included
Metadata + pricing feeds Manual $1K - $5K/mo Included
Security + spam detection Must build Included
Cross-chain scaling Manual & costly Complexity multiplies One query param
Time to launch 1 day 3-18+ months ~1 hour
Typical Monthly Outlay ~$20K-$70K/month + hiring + maintenance $299-$4,500/month scale-dependent

Total Cost of Ownership (TCO)


Most teams spend more on the first engineer needed to maintain the system than the entire Moralis platform costs for the year.

One blockchain data engineer $120K-$240K /year fully loaded

Annual Moralis subscription starts at $588 /year

Total cost of ownership comparison between building blockchain data infrastructure in-house and using Moralis

Layered Data Stack
(What You'd Otherwise Have to Build)

#4

Token balances are just one data type. A production-grade data layer requires 60+ specialised data pipelines.

  • Application-Ready Data (what UI & product teams need)
  • Pricing, Metadata, Spam/Scam Detection
  • Unified Balances & Portfolios Across Chains
  • Indexing (logs, traces, re-org safety, historical sync)
  • Nodes / RPC Access (Node providers stop here)
Diagram illustrating a layered blockchain data stack from nodes and indexing to application-ready data

Security, Reliability
& Compliance (SOC 2 Type II)

#5

Operating a blockchain data indexing platform isn't just an engineering task - it's a security and compliance responsibility.

Most internal teams under-estimate the ongoing operational and compliance overhead required to keep such a system secure and audit-ready.

Moralis maintains:

SOC 2 Type II Certification Active and audited annually Our internal systems, data handling, access controls, logging, monitoring, and change management are continuously validated by an independent auditor
Continuous chain data validation Automated Detects and corrects chain reorgs, indexing anomalies, metadata drifts
No keys, no signing, no custody Architectural Zero risk of wallet compromise / asset interaction

Why this matters in Build vs Buy

If you self-build:

  • You must design and maintain access controls
  • You must maintain change management procedures
  • You must pass (and pay for) security audits annually
  • You must create and maintain incident response playbooks
  • You require 1-2 dedicated security + compliance engineers
  • You must engage with external audit firms at high ongoing cost

If you use Moralis

  • We provide the platform already security-certified and continuously audited.
  • Your team inherits this assurance - instead of needing to build it.

Time-to-Market

#6

In Web3, timing is everything. First movers capture developer mindshare and ecosystem adoption.

TIME TO MVP
6-12 months
TIME TO PRODUCTION GRADE
12-24+ months
TIME TO MVP
~1 hour
TIME TO PRODUCTION GRADE
1-4 weeks incl. QA

Shipping 6–12 months earlier often determines:

  • Ecosystem adoption

    First-mover advantage

  • Market positioning

    Category leadership

  • Developer mindshare

    Community growth

Conclusion

#6

In Web3, timing is everything. First movers capture developer mindshare and ecosystem adoption.

Nodes are for raw blockchain access.

Moralis is for production-ready blockchain data.

Moralis replaces:

  • 1-3 full-time engineers
  • Multi-region node infra
  • Continuous indexing maintenance
  • Metadata & pricing synchronization
  • Security / spam filtering logic

Usage Calculator

Not sure which plan fits? Enter your expected API usage and we’ll help estimate your CU needs and suggest a matching plan. Please note this is a rough estimate, not a formal quote.

500K
50 RPS

Based on an average of 72 CUs per API request.

36M CUs

1,100 CUs/second

Customize

Average CUs: 72

Average CUs throughput: 22

Select the endpoints you plan to use to get a more accurate estimate of your average CU usage per request.

Need a custom quote?

Can’t find your endpoints above? Reach out to our sales team - we’ll put together a custom quote for you.

Contacts Sales View all 80+ endpoints

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Includes free access to our ROI calculator

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