enterprise
intermediate

Rust Data Engineering Pipeline

Solution Components

rust
rust
data-engineering
data-engineering
kafka
kafka
tokio
tokio
polars
polars

Cloud Cost Estimator

Dynamic Pricing Calculator

$0 / month
Compute Resources
$ 15
Database Storage
$ 25
Load Balancer
$ 10
CDN / Bandwidth
$ 5
* Estimates vary by provider & region
%% Autogenerated infra-rust-data graph TD classDef standard fill:#1e293b,stroke:#38bdf8,stroke-width:1px,color:#e5e7eb; classDef c-actor fill:#1e293b,stroke:#e5e7eb,stroke-width:1px,stroke-dasharray: 5 5,color:#e5e7eb; classDef c-compute fill:#422006,stroke:#fb923c,stroke-width:1px,color:#fed7aa; classDef c-database fill:#064e3b,stroke:#34d399,stroke-width:1px,color:#d1fae5; classDef c-network fill:#2e1065,stroke:#a855f7,stroke-width:1px,color:#f3e8ff; classDef c-storage fill:#450a0a,stroke:#f87171,stroke-width:1px,color:#fee2e2; classDef c-security fill:#450a0a,stroke:#f87171,stroke-width:1px,color:#fee2e2; classDef c-gateway fill:#2e1065,stroke:#a855f7,stroke-width:1px,color:#f3e8ff; classDef c-container fill:#422006,stroke:#facc15,stroke-width:1px,color:#fef9c3; subgraph stream-layer ["Streaming Layer"] direction TB kafka["Kafka / Redpanda
message-broker
Event Log"] class kafka standard ingester["
Rust Consumer (Tokio)serviceAsync I/O
"] class ingester c-compute end subgraph compute-layer ["Compute Layer"] direction TB processor["
Data Processor (Polars)functionETL / Aggregation
"] class processor standard api["
Query API (Axum)serviceServes Aggregates
"] class api c-compute end %% Orphans devices["IoT / Clickstream
external"] class devices standard s3["
Data Lake (S3)storageParquet/Delta
"] class s3 c-storage %% Edges kafka -.-> devices ingester -.-> kafka processor -.-> ingester s3 -.-> processor api -.-> s3

Rust Data Engineering Pipeline

When data correctness and latency are paramount, Rust replaces Python/Java. This architecture ingests events from Kafka, processes them with Polars/Tokio, and writes to Delta Lake.

Core Components:

  • Ingester (Rust): Tokio-based async service consuming high-velocity Kafka topics.
  • Processor (Rust + Polars): In-memory columnar data frame processing for real-time aggregations.
  • Kafka / Redpanda: Durable event log.
  • Object Store (S3): Long-term storage in open formats (Parquet/Delta).

Tech Stack

Component Technology
Segment enterprise
Language rust
Concurrency tokio
Data Frame polars
Stream kafka
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