Alchemy’s Smart WebSockets are commonly used to receive real-time push notifications for on-chain events such as new blocks, mined and pending transactions, address activity, and more. The setup process is straightforward and its performance meets the requirements of applications that operate at small and medium scales. This websocket system begin to show limitations when your application scales and you require sub-second latency combined with enterprise reliability and the capacity to track multiple tokens simultaneously.
In this article, we’ll cover the top alternatives to Alchemy WebSockets, starting with the most full-featured real-time streaming platform available today.
Bitquery is a real-time blockchain data streaming platform that provides users three distinct streaming technologies, each optimized for different latency and scale requirements. They are:
- Real-time GraphQL Subscriptions (WebSocket API)
- Kafka Streams (High performance)
- CoreCast (gRPC Streams)
- Real-time GraphQL Subscriptions (WebSocket API)
Bitquery provides users real-time cryptocurrency data through its WebSocket-based GraphQL subscriptions, which offers strong filtering and customization features. Developers can stream data by connecting to the websocket endpoint, and then customize responses within the GraphQL query.
In addition to OHLCV data for specific time intervals, the same stream can include data like price changes, trade counts, buy vs. sell activity, and detailed volume breakdowns.
It also offers a rich ecosystem of Streams, APIs, and sample applications built on top of this data, enabling developers to:
- Analyze tokens: Tools like the Pump.fun Token Sniffer provide holder distribution, transfer vs. purchase patterns, top holders, and bonding curve metrics.
- Monitor liquidity: The Realtime Liquidity Drain Detector monitors DEX pools in real time via Kafka and alerts on significant liquidity drops.
- Score DeFi portfolios: The DeFi Portfolio Scorer calculates a DeFi Strategy Score (25–100) based on transaction count, protocol usage, and asset diversity.
- Build charts: TradingView with Realtime Data integrates real-time OHLCV via Bitquery subscriptions directly into TradingView charts, with a ready-to-use TradingView SDK available on npm.
This flexibility makes it well suited for crypto trading applications, DeFi dashboards, and blockchain analytics platforms.
Latency
Bitquery’s WebSocket streaming delivers real-time market data with an average latency of approximately 1,664 ms in a 1-second OHLCV test. This means each candle is received about 0.67 seconds after the interval closes. While the data arrives within a couple of seconds and is fast enough for dashboards, analytics platforms, and charting applications.
- High completeness: Enterprise-grade data coverage with up to 99.9% uptime, real-time validation, and automatic outlier detection.
- No message retention/replay: It depends on persistent connection with at-most-once delivery.
- Excellent for filtered, pre-processed feeds: Very high filtering capability (addresses, tokens, pools, USD values, complex conditions) without requiring client-side aggregation.
Bitquery Kafka Streams provide developers real-time blockchain event data, which delivers raw, high-volume streams directly from BitQuery’s ingestion pipeline as compact binary Protobuf messages.Kafka streams push unfiltered data, including transactions, token transfers, DEX trades, and mempool activity, making them best for high-frequency trading (HFT), MEV searchers, arbitrage bots, and others where minimal latency and complete message delivery are critical.
Kafka streams are organized into structured topic naming conventions which follow the pattern
For EVM chains, examples include:
Broadcasted (Mempool-level):
*.broadcasted.transactions.proto → ParsedAbiBlockMessage
*.broadcasted.tokens.proto → TokenBlockMessage
*.broadcasted.dextrades.proto → DexBlockMessage
*.broadcasted.raw.proto → BlockMessage
Other supported chains such as Polygon, Solana, and Tron follow the same structure. Multi-chain topics like trading price streams are also available for cross-chain market data. Broadcasted topics are especially important for detecting transactions before block confirmation, which is important for latency-sensitive strategies such as liquidation monitoring or MEV execution.
For latency, Bitquery Kafka streams deliver sub-second (often
Data Quality & Reliability
Kafka streams are designed for enterprise-grade reliability and scalability:
- Message retention allows consumers to recover from temporary downtime
- Offset tracking enables replay from a specific position
- Consumer groups allow horizontal scaling
- High throughput supports large volumes of blockchain events
Because Kafka delivers complete topic data, consumers must handle ordering, deduplication, and filtering within their own systems. However, this architecture ensures no silent data drops and supports durable, continuous stream processing.
Mempool Handling
Kafka topics with .broadcasted contain pending transaction data before block confirmation. This allows monitoring of mempool activity such as frontrunning attempts, token creation, or liquidation events with minimal delay. Because broadcasted topics stream directly from Bitquery’s ingestion pipeline in Protobuf format, they typically offer lower latency than confirmed block topics.
Pricing at Scale
Bitquery offers unlimited blockchain data streaming with no compute unit charges and no per-stream fees, combined with a flexible points-based API model that ensures you only pay for what you actually use. It supports unlimited active streams, scalable API calls without throttling, and multiple data interfaces including SQL, Cloud, Kafka, WebSocket, and GraphQL. It also offers 24/7 access to its engineering team, priority support via Slack and Telegram, dedicated onboarding, and custom SLAs for enterprise needs.
Bitquery provides users ultra-low latency blockchain data through its gRPC-based CoreCast streams, which offers efficient binary serialization using Protobuf. Developers can stream data by connecting to the endpoint corecast.bitquery.io with an API token generated from API Access Tokens. It allows users to apply basic server-side filtering by addresses, tokens, pools, and value thresholds.Currently focused on the Solana blockchain, CoreCast is ideal for building Solana trading bots, MEV applications, real-time DeFi protocols, Jupiter aggregator monitoring, and Telegram bots.
Latency
CoreCast delivers the fastest streaming experience among Bitquery’s three technologies, with latency under 100ms (
Data Quality & Reliability
- Lightweight and fast: Protobuf-based typed contracts ensure efficient, compact data transmission optimized for backend applications and trading strategies.
- Basic server-side filtering: Supports filtering by addresses, tokens, pools, and thresholds reducing unnecessary data transfer.
QuickNode Streams is a powerful data ingestion and streaming solution designed for web3 applications. It allows users collect, process, and store both raw and filtered blockchain data in real-time and historically. It provides the infrastructure for users to create robust data pipelines with features like batching, backfill, and continuous streaming. This is suitable for building tools such as building indexers, analytics platforms, or real-time dashboards
Key features include:
- JavaScript-Based Filtering – Users can define custom filters in JavaScript to process and transform blockchain data on Quicknode’s infrastructure before it reaches the destination.
- Flexible Data Ingestion – Streams supports both raw blockchain data and filtered datasets. Use JavaScript filters to extract exactly the data needed for indexing or analytics use case, processed on its infrastructure.
- Historical & Real-time Processing – Users can build comprehensive data pipelines that handle both historical backfills and real-time streaming, perfect for indexers and analytics platforms.
- Guaranteed Data Delivery – Streams ensures exactly-once delivery of blocks, receipts, and traces in finality order, maintaining data integrity for indexing and analytics systems.
- Efficient Batch Processing – Configure data batches of multiple blocks for optimal historical data ingestion.
- Operational Transparency – Users can monitor data pipelines through detailed logs and performance metrics, with usage tracking for cost optimization.
Helius offers multiple streaming solutions for real-time Solana data:
LaserStream: LaserStream is a next-generation streaming service purpose-built for developers who need reliable, low-latency Solana data.
It delivers on-chain events (transactions, slots, blocks, accounts, and more) directly to applications with industry-leading reliability, performance, and flexibility.The LaserStream nodes tap directly into Solana leaders to receive shreds as they’re produced, delivering ultra-low latency data to intended application.
Websocket: Helius also provides a robust WebSocket (WSS) interface for real-time Solana blockchain event streaming, allowing developers to subscribe to updates such as account changes, program interactions, transaction confirmations, and more. This is particularly useful for building responsive applications like trading bots, wallets, or monitoring tools that need sub-second notifications.The WebSocket methods are powered by the same high-performance infrastructure as Helius’s LaserStream, delivering up to 200 ms faster responses compared to standard Solana RPC WebSockets.
Moralis Streams is a real-time event streaming service that sends blockchain activity to app backends through webhooks, users don’t need to poll nodes. Moralis Streams listens for on-chain events such as wallet transfers or contract logs and delivers them instantly when they match the stream rules made by users. A stream’s lifecycle can be managed by creating it, updating its configuration (such as webhook URL or filters), pausing or resuming it, and monitoring its status.
Each stream has a lifecycle state; active, paused, error, or terminated that tells users whether it’s currently sending events and webhooks.
Regions can be updated to optimise delivery latency and adjust filters anytime without deleting the stream. If a stream stays in an error state too long, it gets automatically terminated and stops sending events. This flexible lifecycle management makes it easy to build reliable, real-time blockchain integrations
Chainlink Data Streams delivers low-latency market data offchain verifiable onchain. This provides dApps with on-demand access to high-frequency market data backed by decentralized and transparent infrastructure.
Chainlink Data Streams makes use of a pull-based design that preserves trust-minimization with onchain verification.
Data Streams are offered in several report formats, each designed for distinct asset classes.
Sub-Second Data and Commit-and-Reveal
Chainlink Data Streams supports sub-second data resolution for latency-sensitive use cases by retrieving data only when needed. Users can combine the data with any transaction in near real time.
High availability and resilient infrastructure
Data Streams API services use an active-active multi-site deployment model across multiple distributed and isolated origins. This architecture ensures continuous operations even if one origin fails, delivering robust fault tolerance and high availability.
For real-time streaming applications, the SDKs support High Availability (HA) mode that establishes multiple simultaneous connections for zero-downtime operation.
When enabled, HA mode provides:
- Automatic failover between connections
- Report deduplication across connections
- Automatic origin discovery to find available endpoints
- Per-connection monitoring and statistics
Key capabilities
- Sub-second Latency: Pull data on-demand with minimal delay
- Cryptographic Verification: Verify data authenticity onchain when needed
- Multiple Access Methods: REST API, WebSocket, or SDK integration
- High Availability: Multi-site deployment ensures 99.9%+ uptime
How to Choose the Right Alternative
The right choice depends on what you’re building today and how large it needs to become:
If you’re building a web app or dashboard and want something close to Alchemy WebSockets with more data depth: start with Bitquery’s GraphQL Subscriptions, and you get advanced filtering, USD price calculations, and multi-chain support in one subscription interface.
If latency is critical and you cannot drop messages: migrate to Bitquery Kafka. The sub-500ms delivery with at-least-once guarantees and 4-hour message retention means your application will never fall behind or miss an event even during chain congestion or connection drops.
