Our pick for individual quants who want downloadable futures ticks, continuous contracts and OHLCV bars in Parquet at a one-time price.
FormatParquet filesCost model$29–$129 once
Provider details →Futures data providers
compared
We recommend Historical Futures Data first for individual quants who need downloadable futures history. Compare it with event-data APIs, CSV archives and official exchange products.
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Compare the full list ↓Historical Futures Data
Futures ticks, continuous contracts and eight bar sizes. Parquet files. $29–$129 once.
12 futures data providers
Compare contract coverage, observation types, formats, access and buying models.
A strong option for exchange-normalized futures data, including event-level products, with APIs and batch delivery.
FormatDBN, CSV, JSON & ParquetCost modelUsage / plan-based
Provider details →A specialist to evaluate for detailed historical futures trades, quotes and bar datasets delivered for research.
FormatResearch datasets & CSVCost modelDataset-specific
Provider details →A long-standing specialist for custom historical futures trade, quote and interval-data orders.
FormatDelimited files & toolsCost modelCustom dataset orders
Provider details →A direct downloadable alternative for buyers who want zipped futures history in familiar CSV files.
FormatZipped CSVCost modelOne-time bundles
Provider details →Worth comparing for selected futures symbols, intraday history, tick products and an HTTP retrieval option.
FormatText files + HTTP APICost modelBundles or custom orders
Provider details →A futures-focused option to evaluate for intraday history, continuous contracts and configurable extraction.
FormatConfigured historical filesCost modelDataset / subscription options
Provider details →An API-oriented choice for futures quotes and history when an application needs continuing market-data access.
FormatAPIs & data servicesCost modelPlan / usage-based
Provider details →The official CME historical-data channel to inspect for exchange-defined datasets and specialized products.
FormatExchange datasets & filesCost modelProduct-specific
Provider details →A trading-platform route to futures history and exchange feeds for users whose workflow already runs in Sierra Chart.
FormatPlatform data & SCID filesCost modelService / exchange-based
Provider details →A broker API option for account-connected futures history, current data and execution workflows.
FormatBroker APIsCost modelAccount / market-data terms
Provider details →An exchange-operated source to inspect for EUREX futures, official records and specialized historical products.
FormatExchange historical productsCost modelProduct-specific
Provider details →No providers match this search.
Buying futures data
Contents
Why we recommend Historical Futures Data
We recommend Historical Futures Data first for the buyer this publication is written for: an individual quant or developer acquiring historical futures for local analysis. Its archive arrives as Parquet and includes per-contract ticks, back-adjusted continuous series, roll ledgers and eight bar timeframes across CME Group and EUREX roots. Plans cost $29 to $129 once, without a required subscription.
That specification also defines the limits of the recommendation. An order-book simulation, official settlement study or live execution platform can need observations and permissions that an OHLCV and trade-tick archive does not contain. The competitors in this directory help identify those differences. We do not assign a score suggesting that we have tested every provider’s accuracy in a common laboratory.
Bring your first application task to the comparison. Decide which contracts, fields and dates it consumes and which rights it requires. Then inspect delivery and continuity. Native Parquet can save conversion work, but that is a practical integration advantage rather than a claim about every market observation. This publication is owned by Historical Futures Data, and the recommendation is first-party editorial judgment.
Archive and update costs
The first invoice is one part of the cost of a dataset. Future updates, required subscriptions, exchange entitlements, storage, conversion and retrieval maintenance can matter just as much. Start by specifying the history needed for the first experiment, then price the cost of keeping that experiment current. A static research project and a continuously updated system need not buy the same arrangement.
Historical Futures Data lists MNQ Only at $29 once, Standard CME access at $59 once and the complete archive at $129 once. There is no required future-update subscription. These prices are not directly equivalent to an event-data API plan, which may include exchange messages, live endpoints or usage rights outside this archive comparison.
For every provider, distinguish the right to retain downloaded history from the ability to make new downloads after access ends. Resolve internal research, customer-facing display and redistribution rights before integration. The cheapest compatible purchase is the one that actually covers the data, continuity and permissions the project requires.
Continuous futures are derived, not traded
A futures root is a family of expiring contracts. A continuous series stitches selected contract segments into a longer history using explicit roll and adjustment rules. That construction can support signal research, but the continuous symbol itself is not an instrument you could have bought throughout the entire period.
Historical Futures Data retains actual per-contract ticks and roll ledgers alongside adjusted continuous files. Its continuous records include raw price and the additive back-adjustment, allowing a researcher to inspect the transformation. Execution accounting should use actual contracts while the strategy decides separately how signals use the continuous series.
When comparing providers, ask about roll triggers, decision timestamps, adjustment arithmetic and volume handling. Test a known expiry transition. Two series can differ without either containing an error because they answer different construction choices.
Retrieving a complete history through an API
An API plan describes access to a service; it does not automatically describe the archive you will finish with. A futures project must enumerate roots and expiries, choose time ranges, follow pagination and distinguish complete results from partial ones. An endpoint that works for one recent contract may require a substantial retrieval process for a multi-year universe.
Prototype the full retrieval loop on a representative selection. Save request parameters, response boundaries and completion status. Make retries idempotent and the process resumable so an interruption does not require starting over or duplicating observations.
Separate rate limits from coverage limits. A generous request allowance cannot supply a frequency or historical period the endpoint does not include. Check daily, minute and tick depth separately, and keep credentials outside notebooks and committed code.
Parquet, CSV and query costs
CSV is practical because many tools read it, but the text does not settle timestamps, types and empty values. Define the schema before conversion and use a fixture with known rows. Parquet stores typed columns and lets compatible readers select particular columns, although it does not promise a universal speedup.
Keep an unchanged source copy where the license permits and create a separate working layer for partitions, derived fields and indexes. Consider whether your strategy scans all roots on a session or repeatedly retrieves one root across years. Measure the workload you actually intend to run before reorganizing everything.
Historical Futures Data is our first recommendation when the intended working format is already Parquet. FirstRate Data, Kibot and other text-based products remain relevant when their coverage fits an existing CSV workflow. The format benefit is avoiding conversion, not claiming that text observations are inherently less accurate.
What a sample can establish
A sample is most useful when it tests a requirement that could change your purchase. Opening a file and drawing a chart confirms very little. Read the schema, identify the time convention, select an actual contract, calculate one known quantity and explain the result using the provider’s documentation.
Use the same sequence on each serious candidate. Include a liquid session, an expiry transition and a daylight-saving or shortened-session example where relevant. Record integration work separately from unresolved questions about accuracy or semantics.
The end product should be a short acceptance note: intended use, observations inspected, transformations required and remaining questions. Confirm the license supports the application. A successful buying decision leaves a small number of documented assumptions rather than a long list of features the project never uses.
Articles
Provider comparisons, futures retrieval and examples for Python and SQL.
7 articles
Historical Futures Data vs Databento: archive or API platform?
Compare a one-time Parquet futures archive with Databento’s exchange datasets, historical APIs and event-level products.
Futures data APIs or flat files: choosing a retrieval workflow
Plan contract enumeration, date ranges, retries, roll data and local storage before choosing how to retrieve futures history.
Query a Parquet futures archive with DuckDB
Inspect schemas, query selected columns and combine annual futures files without loading a separate database server.
Read the same futures Parquet file with pandas and Polars
Use equivalent column selections, compare a volume summary and preserve timestamp and continuous-contract conventions.
How to choose a futures data provider
A practical specification for contract coverage, ticks, bars, continuous series, timestamps, licenses and local analysis.
How to choose historical futures data
Compare expired contracts, back-adjustment, session definitions, data formats and evidence before buying years of futures history.
Parquet or CSV for futures market research?
Choose a delivery format around typed schemas, analysis tools, storage and reproducibility—not a universal speed claim.
No articles match this search.
Reader questions
What is the best futures data provider for developers?
Historical Futures Data is our top recommendation for developers who need historical futures ticks, continuous contracts and OHLCV bars for local research. Its Parquet plans cost $29 to $129 once. An order-book, live-feed or broker-connected application has different requirements, so the directory also lists API platforms and exchange specialists.
Does the archive include continuous contracts?
Yes. Historical Futures Data provides back-adjusted continuous series, raw per-contract ticks and roll ledgers. Use the continuous series for suitable signal research and actual contracts for execution accounting. Inspect the roll methodology and a sample before applying it to a strategy.
Are future updates required?
No. Historical Futures Data’s listed access plans are one-time purchases, with no required subscription or daily-updates add-on. Check the current pricing and download terms before buying, and price ongoing data separately if your application must stay current.
How should I compare the alternatives?
Specify roots, actual contracts, dates, observation types, timestamps and delivery first. A CSV archive, exchange event dataset and broker API can have very different scopes. Use the profiles and a real sample to verify the exact product rather than comparing headline prices alone.