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.BitqueryBitquery 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.LatencyBitquery’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.Data Quality & Reliability 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.Kafka Streams (High-Performance)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 . and .broadcasted.. Broadcasted topics provide mempool-level data and are available for most blockchains, offering lower latency as transactions are streamed before block commitment.For EVM chains, examples include:Broadcasted (Mempool-level):*.broadcasted.transactions.proto → ParsedAbiBlockMessage*.broadcasted.tokens.proto → TokenBlockMessage*.broadcasted.dextrades.proto → DexBlockMessage*.broadcasted.raw.proto → BlockMessageOther 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.LatencyFor latency, Bitquery Kafka streams deliver sub-second (often < 500 ms) end-to-end latency for parsed events like DEX trades, token transfers, and blocks due to a shorter data pipeline, efficient Protobuf format, and direct streaming from Bitquery’s blockchain ingestion infrastructure. Kafka streams deliver raw, complete data with guaranteed message delivery and replay capability. Overall, Kafka streams are the preferred choice for latency-sensitive, high-throughput applications.Data Quality & ReliabilityKafka streams are designed for enterprise-grade reliability and scalability:Message retention allows consumers to recover from temporary downtimeOffset tracking enables replay from a specific positionConsumer groups allow horizontal scalingHigh throughput supports large volumes of blockchain eventsBecause 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 HandlingKafka 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 ScaleBitquery 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.CoreCast (gRPC Streams)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.LatencyCoreCast delivers the fastest streaming experience among Bitquery’s three technologies, with latency under 100ms (