Database sinks: Postgres, MySQL, ClickHouse
Point a recipe at your own Postgres, MySQL, or ClickHouse database and the sink continuously lands ready-to-query tables. Moralis does the heavy lifting in the recipe, decoding, enrichment, and reorg correction, so you query a production-grade dataset inside your own stack. Use this if you want queryable tables in a database you control, especially for request/response needs like “a wallet’s balances.” See Database sinks for choosing between the three.Streaming: Kafka, RabbitMQ, SQS
Consume feeds through supported streaming interfaces using Kafka-compatible, RabbitMQ/AMQP, or SQS-compatible clients, depending on the feed and current availability. Bring the consumers you already run instead of building a new ingestion path. Use this if you already operate an event pipeline and want onchain data flowing through it. See Streaming.Warehouse access: Apache Iceberg
Query feed data from your warehouse or notebooks through Apache Iceberg-compatible workflows, on platforms such as Snowflake, BigQuery, Databricks, Spark, Trino, DuckDB, Pandas, and dbt, without moving the data through your own ETL first. Use this if your analytics or data team lives in a warehouse or notebook environment. See Warehouse access.Direct reads: REST/HTTP and Arrow Flight
Read feed data directly over REST/HTTP for simple pulls, or over Arrow Flight (gRPC) for high-throughput columnar transfers straight into analytical tooling. Use this if you want to pull data on demand without running a sink or a streaming consumer. See Direct reads.Which path fits your workload?
Early access. Data Feeds is in early access, and interface availability can vary by feed and chain.
Confirm current availability for the protocols and platforms you plan to use when you onboard, see
Early access.
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