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Why is Binance Funding Fee is showing empty. Previously, I was able to see positive and negative funding fee charged! #Query
Blockchain Developers Face Unexpected Costs with Google Cloud's BigQuery
#BLOCKCHAIN
#QUERY #GOOLECLOUD #ETH #BTC
Blockchain developers leveraging Google Cloud’s BigQuery are running into an unforeseen challenge: unexpectedly high costs. While BigQuery has long been praised for its ability to handle vast amounts of blockchain data with speed and scalability, many developers are realizing that the pay-as-you-go model can become expensive if not managed carefully.
BigQuery provides open access to datasets for popular blockchains like Bitcoin, Ethereum, and Polygon, enabling developers, analysts, and researchers to run powerful queries on-chain. This has been a game-changer for projects that require real-time insights into transactions, token movements, or smart contract activity. However, every query executed consumes resources, and the charges can add up quickly—especially for complex or repetitive queries.
For smaller blockchain startups and independent developers, these unexpected bills are proving to be a serious concern. Many report that even exploratory queries during testing phases can generate significant costs, cutting into budgets that were originally meant for development and deployment.
To mitigate these issues, experts suggest optimizing query structures, using table partitions, and caching frequent queries. Some teams are even moving portions of their workloads to alternative solutions or open-source indexing tools to reduce reliance on BigQuery’s premium services.
Ultimately, while Google Cloud’s BigQuery remains a powerful tool for blockchain innovation, developers must weigh its convenience against potential financial strain. Cost transparency, better budgeting practices, and exploring hybrid data solutions may be the key to ensuring blockchain projects thrive without being derailed by cloud expenses.
#BLOCKCHAIN
#QUERY #GOOLECLOUD #ETH #BTC
Blockchain developers leveraging Google Cloud’s BigQuery are running into an unforeseen challenge: unexpectedly high costs. While BigQuery has long been praised for its ability to handle vast amounts of blockchain data with speed and scalability, many developers are realizing that the pay-as-you-go model can become expensive if not managed carefully.
BigQuery provides open access to datasets for popular blockchains like Bitcoin, Ethereum, and Polygon, enabling developers, analysts, and researchers to run powerful queries on-chain. This has been a game-changer for projects that require real-time insights into transactions, token movements, or smart contract activity. However, every query executed consumes resources, and the charges can add up quickly—especially for complex or repetitive queries.
For smaller blockchain startups and independent developers, these unexpected bills are proving to be a serious concern. Many report that even exploratory queries during testing phases can generate significant costs, cutting into budgets that were originally meant for development and deployment.
To mitigate these issues, experts suggest optimizing query structures, using table partitions, and caching frequent queries. Some teams are even moving portions of their workloads to alternative solutions or open-source indexing tools to reduce reliance on BigQuery’s premium services.
Ultimately, while Google Cloud’s BigQuery remains a powerful tool for blockchain innovation, developers must weigh its convenience against potential financial strain. Cost transparency, better budgeting practices, and exploring hybrid data solutions may be the key to ensuring blockchain projects thrive without being derailed by cloud expenses.
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Wormhole Query: Request data from any blockchain, anytime! 📊🔍
By July 2025, Wormhole Query is yet another important addition to the ecosystem, allowing dApps to request data from any connected blockchain on demand. This addresses the issue of "data fragmentation" and enables smart contracts to access real-time information from outside their native chain.
Cross-chain analysis: Allows dApps to aggregate data from different blockchains for more comprehensive analysis.
Enhanced dApps: Gives developers the ability to create more complex and information-rich applications.
Next-generation oracles: Wormhole Query can serve as the foundation for more dynamic and decentralized oracle solutions. Wormhole continues to expand its capabilities not only for asset transfer but also for exchanging arbitrary data between networks.
#Wormhole #Query #Web3
By July 2025, Wormhole Query is yet another important addition to the ecosystem, allowing dApps to request data from any connected blockchain on demand. This addresses the issue of "data fragmentation" and enables smart contracts to access real-time information from outside their native chain.
Cross-chain analysis: Allows dApps to aggregate data from different blockchains for more comprehensive analysis.
Enhanced dApps: Gives developers the ability to create more complex and information-rich applications.
Next-generation oracles: Wormhole Query can serve as the foundation for more dynamic and decentralized oracle solutions. Wormhole continues to expand its capabilities not only for asset transfer but also for exchanging arbitrary data between networks.
#Wormhole #Query #Web3
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