Retrieve large historical datasets through the FinFeedAPI Flat Files S3-compatible API.
Instead of paginating through thousands of individual API requests, research teams can browse and download compressed historical files using familiar S3 tools, SDKs, and data infrastructure.
An S3-compatible financial data API provides file-based access to historical datasets using the same interaction model and tooling commonly used with Amazon S3.
Instead of requesting individual records or small time ranges through REST, applications can discover and download complete historical data files.
FinFeedAPI provides S3-compatible access through the Flat Files API, designed for workloads where large volumes of historical data need to be processed efficiently.
FinFeedAPI S3 access is focused on retrieving available historical datasets. It is not intended to function as general-purpose cloud object storage.
REST works well for targeted queries. Large historical workloads are different. Downloading extensive datasets through many paginated API requests adds unnecessary request overhead and makes large-scale ingestion more complicated. This makes Flat Files particularly useful when the workload is defined by large historical ranges rather than individual API queries.
Browse available datasets, identify the files required for your research period, and download them directly.
Flat Files are organized into structured prefixes that make large archives easier to browse programmatically. A typical path identifies Exchange → Dataset → Period → Date. This predictable hierarchy makes it possible to identify and automate downloads for specific exchanges, datasets, periods, and dates.
E-IEXG/T-OHLCV+TP-1MIN/D-20260102.csv.gz| Segment | Meaning |
|---|---|
| E-IEXG | identifies the exchange |
| T-OHLCV | identifies the dataset |
| TP-1MIN | identifies the aggregation period |
| D-20260102 | identifies the date |
| .csv.gz | identifies the compressed CSV format |
The core Flat Files workflow is built around three steps. Supported retrieval-oriented S3 operations include LIST, GET, and HEAD where supported. The interface is intentionally focused on accessing FinFeedAPI datasets rather than creating, uploading, deleting, or managing arbitrary customer objects.
The FinFeedAPI S3-compatible interface works with common tools already used in cloud and data-engineering environments. This means existing S3-based ingestion workflows can be adapted to retrieve FinFeedAPI Flat Files without requiring a proprietary file-transfer client.
Authentication uses your FinFeedAPI API key as the S3 Access Key ID, with S3-compatible request signing. The service supports AWS Signature Version 2 and Version 4 compatibility, and SDK configurations use the us-east-1 region. An unencrypted HTTP endpoint is also available, but HTTPS is the recommended option for production integrations.
https://s3.flatfiles.finfeedapi.com/Examples use the bucket finfeedapi.
http://s3.flatfiles.finfeedapi.com/Suppose a research workflow needs historical 1-minute OHLCV data from IEXG. Instead of requesting each candle individually, the application downloads the historical file and processes the dataset locally or inside its data infrastructure. This pattern scales naturally to research workflows covering many days or larger historical ranges.
The dataset can be browsed through:
s3://finfeedapi/E-IEXG/T-OHLCV+TP-1MIN/Individual daily files can then be selected by date:
s3://finfeedapi/E-IEXG/T-OHLCV+TP-1MIN/D-20260102.csv.gzS3-compatible Flat Files are designed for workloads where bulk historical retrieval is more efficient than individual API requests.
Load historical datasets into research environments for statistical analysis and strategy development.
Download defined historical periods and reuse the same files across repeated strategy simulations.
Build training and validation datasets from historical market data without repeatedly querying an API.
Ingest compressed historical files into internal storage, warehouse, or analytics infrastructure.
Retrieve longer historical ranges without paginating through many REST responses.
Work from date-partitioned files that can be stored and reused across analytical runs.
The difference between REST and Flat Files becomes more important as the requested historical range grows. REST is useful when an application needs a specific resource or targeted time range. Flat Files allow complete historical files to be transferred and processed in bulk.
For example, a multi-month OHLCV workflow may involve discovering the required daily objects once and downloading each compressed file directly rather than issuing large numbers of smaller historical-data requests.
This makes S3-compatible delivery especially useful for data engineering, quantitative research, machine learning, and other workloads where historical volume is the primary requirement.
Efficient Flat Files workflows start by identifying the exact dataset and date range required. The right access method depends on whether the workload is query-oriented or file-oriented.
S3 workflows can involve both object operations and data transfer. The number and size of files therefore matter when planning larger historical workloads. For example, a workflow covering many daily files can include an initial object listing followed by metadata checks and downloads for each required date.
Choose the access method based on the size and shape of the workload. Many systems use both. REST can handle targeted queries and metadata-driven application workflows, while Flat Files provide the larger historical datasets used for research and bulk processing.
| REST API | Flat Files / S3 | |
|---|---|---|
| Access model | Request-response | File-based retrieval |
| Best for | Targeted queries | Bulk historical data |
| Data selection | Parameters and time ranges | Files and prefixes |
| Historical scale | Small to targeted ranges | Large ranges and batch workloads |
| Typical processing | Immediate application response | Local, warehouse, or batch processing |
| Common use cases | Dashboards, applications, specific research queries | Backtesting, ML, warehouses, large-scale research |
FinFeedAPI provides different interfaces for different ways of consuming financial data. The interfaces are complementary rather than interchangeable. A research pipeline, for example, can use MCP to discover available Flat Files, S3 to download them, and REST for smaller targeted queries.
| Interface | Best For | Typical Use Cases |
|---|---|---|
| Flat Files / S3 | Bulk historical retrieval | Backtesting, ML, research, warehouses |
| REST API | Request-response access | Historical queries, snapshots, metadata |
| WebSocket | Continuous live streaming where supported | Exchange rates, SEC filing monitoring |
| JSON-RPC | RPC-style request-response access | RPC-based integrations |
| MCP | AI and tool-driven workflows | Agents, copilots, data discovery |
Move large historical datasets into research, analytics, machine learning, and data infrastructure without relying on thousands of individual REST requests.
Use FinFeedAPI Flat Files with familiar S3-compatible tools and workflows.