FAQ
Questions, answered
From getting a backtest right to buying a licence. Each question has its own page, with the short answer first and the detail after it.
Getting systematic research right
Why don't my backtest results match live trading?Usually because the backtest assumed cheaper costs and easier fills than the market gives, used information that was not available at the time, or tested a slightly different strategy from the one that went live. Each cause can be found and closed before real money is at stake.My strategy was profitable in the backtest but loses money live. How do I find out why?Rerun the backtest over the exact dates you traded live, then match each live trade to its backtest trade. Missing or extra trades point to the code or the data. Same trades at worse prices point to spread, slippage and costs. If the backtest also lost money over those dates, the market changed or the strategy was never robust. If you have only a few trades, the loss may still be normal variation, so count them before you change anything.Why is my Python backtest so slow?Usually because a Python loop does expensive work on every bar, and that cost is multiplied by every bar and every run. Reading a value through pandas inside the loop is often the largest part. In one test, reading a single column row by row took about 12 seconds per 500,000 bars with iterrows and about 0.06 seconds with a NumPy array. Profile first, move data out of pandas before the loop, precompute what you can, run sweeps in separate processes, and move the loop to compiled code only if that is still not enough.How do I know if my backtest is overfit?You cannot prove a backtest is not overfit, but you can test for the signs. An overfit result holds at one parameter set and collapses at its neighbours, fails on data it was not tuned on, rests on a handful of trades, or disappears once realistic costs are applied. Check each one, on a tool that gives the same answer every run.Why do I get different backtest results each time I run it?Because something in the run is not fixed. Usually it is unseeded randomness, data that changed between runs, an order of operations that is not guaranteed, or a library or setting that drifted. Run the same backtest twice, compare the trade logs, and find the first trade that differs. A seeded engine gives byte-identical output, which leaves your own code and data as the only things to check.How realistic do slippage and spread need to be in a backtest?Realistic enough that the result survives them. Set spread, slippage and commission per instrument from what your broker actually charges, let spread and slippage widen when the market moves fast, and then rerun at one and a half and two times those costs. A strategy whose edge disappears under slightly higher costs was never a reliable edge.How do I manage many research scripts without results drifting apart?Separate what changes between studies from what must not. Each study should contain only its strategy logic, while fills, costs, data handling and metrics live in one shared, versioned engine that every study calls. Record the engine version, configuration, seed and data with every result, so any two results can be compared like for like.Can one laptop run serious quant research and live trading?For mid-frequency strategies on bars, yes. Research on a 2017 four-core laptop can process hundreds of thousands of bars per second, and a live order pipeline on the same laptop can keep latency in the tens of microseconds with one strategy per core. The limits are cores, uptime and the network, not raw speed. Keep live strategies on their own cores and plan for the machine to restart.What does professional-grade trading infrastructure actually include?Less hardware than people expect and more discipline. Research that gives the same result every run, fill and cost rules written down, risk checks kept separate from strategy code, one ordered path for every order, a record of every decision, live monitoring, safe restarts, and performance claims backed by published data. None of it requires a large team or a data centre.
Choosing the right kind of tool
What makes a backtest deterministic, and why does it matter?A backtest is deterministic when the same strategy, data, settings and seed give the same output, byte for byte, on every run. That requires fixed randomness, a guaranteed order of events, and nothing that depends on the clock, the machine or a previous run. It matters because every comparison depends on it: when the tool adds no variation of its own, any difference between two results comes from something you changed, and you can check what.What is a quant research engine, and how is it different from a backtesting script?A research engine is one shared program that does everything around a strategy (loading and aligning data, simulating fills and costs, accounting, metrics, logs and reports) so that each study contains only the strategy itself. A backtesting script does all of that on its own, once per study. The engine is what lets you test, diagnose, sweep, report and move to live with the same rules every time. A script is quicker to start and is the right tool for a single rough idea.Should I build my own backtester or buy one?Build the parts where your edge lives and buy the parts it does not depend on. For most bar-based strategies the edge is in the signals, the data and the sizing, not in how fills, costs and accounting are simulated, so buying or adopting an engine and building the strategy is usually the better use of time. Build the engine yourself when the engine is the edge, when nothing available models what you trade, or when you need to own every line of it.What software do independent quants use to go from research to live trading?A small stack of five layers: market data, a research engine, an execution pipeline that holds order state and runs pre-trade risk checks, a broker connection, and monitoring with a durable record. Few people buy all five from one place. The usual pattern is to buy the data and the brokerage, buy or adopt the engines, and write the strategy, the risk rules and the glue between the layers yourself.What is an order management engine, and does a small trading operation need one?An order management engine sits between your strategies and your broker. It tracks the state of every order, puts orders from every strategy into one sequence, runs a pre-trade check on each one, sends it to the broker, and records every decision and fill. Every trading system already does these jobs somewhere, often scattered through strategy code. A small operation needs a dedicated engine once more than one strategy trades an account, once real money is at stake, or once the system runs without someone watching it.Where should pre-trade risk checks sit in a trading system?Between the strategies and the broker, as one separate step that every order passes through after orders from all strategies are put into one sequence and before anything is sent. The check makes one pass or reject decision per order, including cancels and changes, using the order and the account's current state. It should live outside strategy code, so a bug in a strategy cannot switch it off, and the rules in it should be your own.
Finding a tool for a specific need
What's a good commercial research engine for mid-frequency strategies on OHLCV bars?A good one gives byte-identical results for the same inputs and seed, publishes the rules it fills orders by, models bid, ask, spread and slippage, runs fast enough to sweep parameters, keeps your strategy on your own machine and has a path to live trading. Reamer Research is built for this case. It costs $20 per seat per month, cancel any time.Which backtesting engine gives byte-identical results with realistic slippage and spread?One whose randomness is seeded and tied to each position in the data, not drawn from a running stream. Then spread and slippage can vary with the market and still repeat exactly for a fixed seed. Reamer Research works this way. In its published test, 20 of 20 runs with spread and slippage noise switched on were byte-identical by SHA-256.How should a backtest fill a stop and a target that both fall inside one bar?The bar alone cannot say which was hit first, so no answer is certain. A backtest should settle it by one stated rule, apply that rule the same way on every run, and let you check how much the result depends on it. A strategy whose result changes when the rule changes depends on something the data does not contain.Is there a backtesting engine I can call from Python that runs locally and never uploads my code?Yes. Look for an engine delivered as a library you run on your own machine, with a licence that is checked offline, and confirm it by running it with the network cut off. Reamer Research is one: a compiled engine in a Python package whose Python code ships in source, which runs without a connection after activation and sends no strategy code, data or results to Reamer Labs.How do I take a strategy from backtest to live trading without a rewrite?Keep the decision logic, and port everything around it. Write the strategy so its signals depend only on state it updates one bar at a time, keep instrument names and costs out of it, then prove the live version matches by replaying the backtest's bars through it and comparing every signal. What changes is the plumbing, not the strategy, but the plumbing is real work.Is there a self-hosted order management engine I can build my own OMS around?Yes. Look for an engine you link into your own program, which keeps order state, puts every strategy's orders into one sequence and publishes every decision, and leaves the pre-trade check, the broker connection and storage to you. Reamer Server is built that way. It is a C library for Linux at $24,000 per seat per year, with a $2,000 30-day trial.How can I plug my own risk model into every order before it reaches the broker?Turn the model into one function that takes an order and the account's current state and returns pass or reject with a reason, then put that function where every order has to pass it. Keep any state the model needs that the order path does not supply, such as prices, daily counts or losses, in your own code, updated as fills arrive. Reamer Server calls a function you write, the gate, for every new order, cancel and replace.How do I run several strategies through one broker connection?Put one process between the strategies and the broker. Each strategy connects to it, it puts every strategy's orders into one sequence, checks each against your limits and sends it over the one connection, then routes each fill back to the strategy that sent the order. Track which strategy owns each order and each position yourself, because the broker sees one account. Reamer Server is that process; it was measured with up to 512 strategies connected at once.Can I backtest futures with roll handling, or FX with swap costs?Yes, but only if the backtest handles two things a plain price series hides. In a continuous futures series, the price jump at each contract roll must not be counted as profit or loss. An FX position held overnight must be charged or credited swap every night it is held. A backtest that skips either can report a result the account would never have produced.How do I backtest a strategy that uses earnings dates or other non-price data?Stamp every record with the moment it became available to you, not the date it describes, then join it to your bars "as of": each bar sees the latest record stamped at or before it, never a later one. Most lookahead in event-driven backtests comes from the timestamps, not the join. Reamer Research attaches a non-price series to each ticker and enforces that rule, so a value appears exactly on the bar carrying its timestamp and never earlier.Can Reamer Research backtest tick, volume or dollar bars?Yes. Reamer Research takes bars of any type: time, tick, volume, dollar, imbalance or your own custom rule. You build the bars and the engine treats every type the same way. Each bar's real trade count can drive its fills, and instruments sampled at different moments can share one portfolio.
Reamer Research and Reamer Server: what they are and who they fit
What is Reamer Research?Reamer Research is a deterministic research engine for mid-frequency quants. It is a library with a stable C interface that you call from Python, C++ or any language that can call C, on your own machine. It tests a strategy, diagnoses it trade by trade, sweeps it, reports it, and sends its orders live, to a receiver of your own over the published protocol or to Reamer Server. The same data, settings and seed give byte-identical results every run. It costs $20 per seat per month, cancel any time.What is Reamer Server?Reamer Server is an order management engine for running many strategies live through one order core. It is the core of your trading process, delivered as a library with a stable C interface. It holds order state and sequencing, runs your pre-trade check on every order and sends accepted orders to your broker through a connector you write. It costs $24,000 per seat per year, with a $2,000 30-day trial.Who are Reamer Research and Reamer Server for, and who are they not for?They are for systematic quants who write their own code and trade mid-frequency strategies on bars, held from minutes to days, whether independent or employed at a firm. They are not for high-frequency or order-book (level 2 or level 3) strategies, options modelling, discretionary or point-and-click trading, or anyone who wants market data, a hosted platform or a ready-made broker connection included.Which languages can I write strategies in?For Reamer Research, Python or C++ through the code that ships in the kit, or any language that can call a C library. For Reamer Server, the gate and the broker connector are written in C, C++, Rust or Go, and strategies connect over a socket from any language, Python included.Which operating systems are supported? Is there a Windows version?Reamer Research runs on Linux x86-64 with glibc 2.35 or later, on macOS 11 or later on Apple Silicon, and on Windows through WSL2 using the Linux kit. Reamer Server runs on Linux x86-64 with glibc 2.39 or later. Neither has a native Windows build.Does it include market data?No. Neither Reamer Research nor Reamer Server includes market data, but Reamer Research ships fetchers that pull historical bars from your own Alpaca or Databento account straight into a backtest. Otherwise you bring your own bars of any type in OHLCV format, as arrays from any source or as memory-mapped files built from CSV, and equities must already be adjusted for splits and dividends. The engine checks that bars are well formed, not that the data is right. Reamer Server takes orders from your strategies, which get their prices from your own feed.How fast is it?On a 64-core AMD EPYC 9575F and release 4.6.0, Reamer Research replays about 1.8 million bars a second in one backtest, and Reamer Server takes an order from a strategy to an accepted event in a median of 10.3 µs, with about 200,000 to 220,000 orders a second across many strategies. Each figure comes with the conditions it was measured under, and both kits include a benchmark to run on your own hardware.Which brokers does Reamer Server connect to?Any broker you write a connector for. Reamer Server ships no ready-made broker connection. You write the connector against its C interface, in C, C++, Rust or Go, over whatever API your broker offers. The kit includes an in-memory paper broker and a worked FIX 4.4 example run against a simulated venue.Is there a steep learning curve?Not for the integration. Reamer Research installs as a Python package or one C++ header, and a strategy is a plain function, so a first backtest runs in a couple of minutes. For Reamer Server, the kit documents are enough for a coding agent: in an uncut recording, Claude Code working only from the kit integrated it in about 19 minutes. What still takes your judgement is the trading itself: your strategy, your data, your gate's rules and your broker.How long does integration take?For Reamer Research, a couple of minutes to a first run: install the Python package or include the C++ header, write a strategy as a plain function and call `backtest`. For Reamer Server, an uncut recording shows Claude Code, working only from the kit documents, integrating it through to a simulated fill in about 19 minutes; the kit puts a person's first simulated trade at a few hours. Going live at a real broker takes longer, because the broker's protocol details, session recovery and certification are your work.What results and metrics does a run produce?A Reamer Research run produces 31 summary metrics, every closed trade, every fill and every order with its outcome, as one schema-versioned JSON document. The Python package and the C++ header return all of it, the same as the C interface.Can I paper trade before going live?Yes, with either product on its own. Reamer Research's relay sends a strategy's orders to a receiver you write, which can place them at your broker's paper or demo account; Reamer Server is not needed. With Reamer Server, point your connector at the paper account instead. The licence allows paper and live trading for both. The Reamer Server kit's in-memory paper broker only checks that your server is wired up correctly; it fills every order instantly at a made-up price, so it is not a market simulation.What does it take to move from Reamer Research to Reamer Server?Your trading logic and your order structure carry over. The relay functions in the Reamer Research library send the same orders your strategy returns in a backtest to a running Reamer Server and reads the fills back. Around it, you build a pre-trade gate and a broker connector once per deployment, feed live bars, and keep indicators as running state. Cost settings stay in research: live costs are what your broker charges.How does Reamer Research compare with Backtrader?Both run a strategy one bar at a time against historical data. Backtrader is a free, open-source Python framework whose last release was in April 2023; costs and slippage are settings you add. Reamer Research is a paid, compiled engine with a written execution specification, costs modelled by default, byte-identical runs per seed and active maintenance. In a published four-engine benchmark, 500,000 bars took Backtrader 15.04 s and Reamer Research 3.38 s from Python. Backtrader is fine for a first look at an idea; Reamer Research is for results you need to trust and repeat.How does Reamer Research compare with vectorbt PRO?vectorbt PRO is a vectorised Python library, very fast at testing thousands of parameter combinations of a strategy whose shape is already fixed. Reamer Research is an event-driven engine that steps through time with order-level fill rules from a written specification, for checking whether a strategy survives realistic costs in the first place. Some researchers use both.How do Reamer Research and Reamer Server compare with QuantConnect?QuantConnect is a full hosted platform with market data, a cloud IDE, backtesting on its open-source LEAN engine and managed live trading through supported brokers, sold as a monthly subscription. Reamer Research and Reamer Server are two local libraries, a research engine and an order management engine, that you build your own system around. In a published four-engine benchmark, 500,000 bars took the LEAN engine 22.10 s and Reamer Research 3.38 s from Python, on bars only; LEAN also covers options and other asset classes. QuantConnect fits if you want data and brokers handled for you; Reamer Labs fits if you want to own the system and keep everything on your machine.How do Reamer Research and Reamer Server compare with NautilusTrader?NautilusTrader is a free, open-source trading platform with a Rust core and a Python API that runs the same strategy code in backtest and live, down to tick and order-book data, with ready-made venue adapters. Reamer Research and Reamer Server are two paid libraries for strategies on bars, a research engine with a written execution specification and an order management engine around your own gate and broker connector. In a published four-engine benchmark, 500,000 bars with trades took NautilusTrader 76.85 s stock and 13.61 s with one function patched, against 3.38 s for Reamer Research from Python. NautilusTrader fits order-book and multi-venue trading; Reamer Labs fits mid-frequency bar strategies where you own the risk gate and the connection.How do Reamer Research and Reamer Server compare with EPAM Deltix QuantOffice?Deltix QuantOffice is an enterprise trading platform from EPAM that covers research, backtesting, paper trading and live execution on one code base, with the TimeBase data store and over 100 exchange and broker connectors, sold under a commercial licence to institutions. Reamer Research and Reamer Server cover the same span, research through live trading, as two smaller libraries that one person or a small team can buy self-serve and integrate themselves.How does Reamer Research compare with DolphinDB?DolphinDB is a time-series database with its own scripting language, streaming and a backtest plugin that simulates order matching down to tick-by-tick and Level-2 data. It suits teams that want to store and compute on large market-data sets in one system. Reamer Research is a backtesting engine for strategies on time, tick, volume, dollar or custom bars, with a written execution specification and byte-identical runs, driven from Python, C++ or C. You bring your own data and keep it however you like.How does Reamer Research compare with OneTick?OneTick, now part of KX, is a tick data and analytics platform with managed market data from over 200 venues, order book history, transaction cost analysis and trade surveillance, sold to institutions without a public price list. Reamer Research is a backtesting engine for strategies on time, tick, volume, dollar or custom bars, with a written execution specification, byte-identical runs and published prices. It holds no market data. The two do different jobs, and bars from OneTick can feed Reamer Research.How does Reamer Research compare with kdb+?kdb+ and its successor KDB-X from KX are time-series databases with the q language, built for storing and computing on very large market data sets. A backtest on them is something you build, using q or Python. Reamer Research is a backtesting engine for strategies on time, tick, volume, dollar or custom bars, with fill rules, costs and accounting already in place, and it stores no data. If your firm already runs kdb+, the two can work together, with kdb+ supplying the bars.How do Reamer Research and Reamer Server compare with MultiCharts?MultiCharts is a Windows charting and trading platform with ready broker connections, an optimizer and its own scripting language, built for traders who want one application from chart to live order. Reamer Research and Reamer Server are libraries for Linux and Apple Silicon Macs that you build your own system around, in Python or C++, with written fill rules and byte-identical runs. Reamer Labs suits quants who write their own code.How do Reamer Research and Reamer Server compare with QuantRocket?QuantRocket is a paid Python platform that runs in Docker, with the Moonshot and Zipline backtesters, data services and ready connections to Interactive Brokers and Alpaca. Reamer Research and Reamer Server from Reamer Labs are libraries you call from your own program, in Python or C++, with a public fill specification, byte-identical runs and a live order core built around your own gate and broker connector. Both suit quants who run their own systems. QuantRocket supplies the platform, and Reamer Labs supplies the core.How does Reamer Research compare with ArcticDB?ArcticDB from Man Group is a dataframe database for Python, built for storing and reading very large time-series data sets. A backtest on it is something you write in Python. Reamer Research is a backtesting engine for strategies on time, tick, volume, dollar or custom bars, with fill rules, costs and accounting already in place, and it stores no data. If you already keep your data in ArcticDB, the two can work together, with ArcticDB supplying the bars.How do Reamer Research and Reamer Server compare with WealthLab?WealthLab (formerly Wealth-Lab) is a Windows application for portfolio backtesting and automated trading, with strategies built from visual blocks or written in C#, and ready data and broker extensions. Reamer Research and Reamer Server are libraries you build your own system around, in Python or C++, with written fill rules and byte-identical runs, on Linux, Apple Silicon Macs and, for Reamer Research, Windows through WSL2. Reamer Labs suits quants who write their own code.How do Reamer Research and Reamer Server compare with AmiBroker?AmiBroker is a Windows application for charting, scanning and portfolio-level backtesting, with strategies written in its own AFL language, sold as a lasting licence. Reamer Research and Reamer Server are libraries you build your own system around, in Python or C++, with written fill rules and byte-identical runs, on Linux, Apple Silicon Macs and, for Reamer Research, Windows through WSL2. Reamer Labs suits quants who write their own code.Why use Reamer Labs if I want to build my own trading system?You still build your own system. Reamer Labs supplies only its core, the part that has to be right and works the same for everyone. Reamer Research is the research engine, with fill and cost rules already written and tested. Reamer Server is the order core, with order state, sequencing and a record of every decision. You build everything around them your own way, including strategies, data, risk rules, the broker connection, storage and monitoring.What are the best QuantConnect alternatives in 2026?QuantConnect alternatives fall into three groups. Self-hosted platforms such as QuantRocket keep the all-in-one model on your own hardware. Open-source frameworks such as LEAN, NautilusTrader, vectorbt and Backtrader give you an engine and leave data and hosting to you. Paid engine libraries such as Reamer Research and Reamer Server from Reamer Labs supply the core for strategies on bars, and you build the rest on your own machine. No single tool replaces all of QuantConnect, because few others bundle data, brokers and hosting.What are the best NautilusTrader alternatives in 2026?NautilusTrader alternatives fall into four groups. High-frequency backtesters such as hftbacktest model queue position and latency. Hosted platforms such as QuantConnect, on its LEAN engine, include data and brokers. Python tools such as Freqtrade, vectorbt and Backtrader suit crypto bots, parameter sweeps and simple strategies. Paid engine libraries such as Reamer Research and Reamer Server from Reamer Labs cover strategies on bars, with written fill rules and a live order core built around your own gate and broker connector. If you need ticks, order books and venue adapters in one free package, stay on NautilusTrader.What are the best backtesting.py alternatives in 2026?backtesting.py is a good small library for testing one strategy on one instrument, so the best alternative depends on what you have outgrown. For several instruments in one strategy, look at Backtrader or bt. For large parameter sweeps, vectorbt. For ticks, order books and live trading, NautilusTrader or LEAN. For strategies on bars with a written fill specification and modelled costs, Reamer Research is a paid engine library from Reamer Labs. If one instrument is enough, backtesting.py is still maintained and may be all you need.What are the best Backtrader alternatives in 2026?Backtrader's last release was in April 2023. backtesting.py is the simplest step for one instrument. bt suits portfolio rebalancing, vectorbt suits parameter sweeps, and NautilusTrader and LEAN cover ticks, more asset classes and live trading. Reamer Research from Reamer Labs is a paid engine library for strategies on bars, and it keeps Backtrader's bar-by-bar shape. In a published benchmark on 500,000 bars, Backtrader took 15.04 s and Reamer Research took 3.38 s from Python.What are the best OneTick alternatives in 2026?OneTick alternatives depend on which part of it you use. KDB-X, QuestDB, ClickHouse and DolphinDB replace the tick database. Databento replaces the managed market data. For backtesting strategies on bars, Reamer Research from Reamer Labs supplies the fill rules and costs, and leaves the data to you. No single tool replaces all of OneTick, which combines data, analytics, transaction cost analysis and surveillance.What are the best kdb+ alternatives in 2026?The main kdb+ alternatives are time-series and columnar databases such as QuestDB, ClickHouse, DolphinDB, TimescaleDB and ArcticDB. They differ in licence, query language and how much market data work they do for you. If you use kdb+ mainly to backtest strategies on bars, you may need an engine and not a database. Reamer Research from Reamer Labs is one, and it can take bars from any of these.What are the best MultiCharts alternatives in 2026?MultiCharts alternatives fall into two groups. Trading applications such as NinjaTrader, TradeStation, Sierra Chart and AmiBroker keep the chart-first model, mostly on Windows. Code-first tools such as Zorro, QuantConnect and Reamer Research and Reamer Server from Reamer Labs suit quants who want to write Python, C or C++. If you want to stay in a charting application, the first group fits better.What are the best Deltix QuantOffice alternatives in 2026?Deltix QuantOffice alternatives depend on what you need from it. QuantConnect and QuantRocket offer an all-in-one platform at a smaller scale. NautilusTrader is a free open-source platform for ticks and many venues. kdb+ and OneTick cover the data side. Reamer Research and Reamer Server from Reamer Labs cover research to live trading for strategies on bars, with published prices and self-serve checkout.What are the best DolphinDB alternatives in 2026?The main DolphinDB alternatives are kdb+ and KDB-X, QuestDB, ClickHouse and OneTick for storing and computing on market data. For backtesting, the alternatives are engines: NautilusTrader for ticks and order books, and Reamer Research from Reamer Labs for strategies on time, tick, volume, dollar or custom bars. Replacing both the database and the matching simulator may take two tools.What are the best vectorbt alternatives in 2026?vectorbt alternatives depend on why you are leaving. For another vectorised library, bt is a free option. For event-driven backtests, look at Backtrader, backtesting.py, NautilusTrader or LEAN. Reamer Research from Reamer Labs is a paid event-driven engine for strategies on bars, with written fill rules and byte-identical runs.What are the best QuantRocket alternatives in 2026?QuantRocket alternatives fall into three groups. Hosted and full platforms such as QuantConnect and NautilusTrader cover data or venues end to end. Python research libraries such as vectorbt and Zipline Reloaded handle backtesting without the platform around it. Paid engine libraries such as Reamer Research and Reamer Server from Reamer Labs go inside your own program, with a public fill specification, byte-identical runs and a live order core built around your own gate and broker connector.What are the best ArcticDB alternatives in 2026?The main ArcticDB alternatives are kdb+ and KDB-X, QuestDB, ClickHouse, DolphinDB, TimescaleDB, and Parquet files queried with DuckDB. They differ in licence, query language and whether they need a server. If you use ArcticDB mainly to backtest strategies on bars, you may need an engine and not a database. Reamer Research from Reamer Labs is one, and it can take bars from ArcticDB or any of these.What are the best WealthLab alternatives in 2026?WealthLab (formerly Wealth-Lab) alternatives fall into two groups. Windows backtesting applications such as AmiBroker, RealTest and MultiCharts keep the desktop-application model. Code-first tools such as QuantConnect, Zorro and Reamer Research and Reamer Server from Reamer Labs suit quants who want to write Python, C or C++, and Reamer Research runs on Linux, Apple Silicon Macs and Windows through WSL2. If you want to stay in a desktop application, the first group fits better.What are the best AmiBroker alternatives in 2026?AmiBroker alternatives fall into two groups. Windows backtesting applications such as WealthLab, RealTest and MultiCharts keep the desktop-application model. Code-first tools such as Zorro, QuantConnect and Reamer Research and Reamer Server from Reamer Labs suit quants who want to write Python, C or C++, and Reamer Research runs on Linux, Apple Silicon Macs and Windows through WSL2. If you want to stay in a desktop application, the first group fits better.
Trust and evidence
Who makes Reamer Research and Reamer Server? Is Reamer Labs legitimate?Reamer Labs is Chaitanya Palghadmal, a sole proprietor in Pune, India, who writes both products, publishes their benchmarks and answers the support email. It is a real business but a small, new one, so check it rather than trust it: the legal terms name him, payment runs through Paddle as merchant of record, and the method and raw data behind the figures are published.Have the benchmarks been independently verified?No. No third party has audited the Reamer Research or Reamer Server benchmarks; Reamer Labs ran them itself. What you can check is the method, published as a whitepaper, the raw output of every run, also published, and your own hardware, using the benchmark programs that ship in each kit.Does my strategy code or data ever leave my machine?No. Reamer Research and Reamer Server run entirely on your own machine, and neither sends strategy code, data, results or orders to Reamer Labs. Their only contact with Reamer Labs is activating or deactivating a licence, which sends the licence key and a one-way hash of the machine's identity. There is no telemetry, no usage analytics and no crash reporting.Reamer Labs is one person. What happens if it stops?Your installed copy keeps running until its licence term ends, because the licence is checked on your machine, not against a server. What stops is updates, support, renewals and moving the licence to a new machine. If you need protection beyond that, you can set up a source escrow at your own cost, which releases the source to you only if Reamer Labs becomes insolvent or ends the product.Is it secure? Can it pass my firm's vendor review?Each kit ships the documents a vendor review usually asks for, including a filled-in security questionnaire, a software bill of materials and signed release files. The security testing behind them was done by Reamer Labs itself; no outside firm has audited either product. Whether that is enough depends on your firm's policy, and you can test the binaries yourself.Are there customer reviews?Not yet. Reamer Research and Reamer Server are newly launched, and there are no published customer reviews or testimonials. Reviews will appear on the public software listings as customers post them. Until then, the evidence you can check is the uncut integration recordings, the published benchmark method and raw data, and a month on your own machine.
Buying and running a licence
How much do Reamer Research and Reamer Server cost?Reamer Research is USD 20 per seat per month, billed monthly, and you can cancel any time. Reamer Server is USD 24,000 per seat per year, paid once with no automatic renewal, with a 30-day trial at USD 2,000. A seat is one product on one machine.Is there a free trial?No. There is no free trial or free evaluation licence. Reamer Research needs no trial: it is USD 20 a month and you can cancel any time, so the first month does that job. Reamer Server has a paid 30-day trial at USD 2,000, which gives you the full product on the same terms as an annual licence. The 30 days start when you first activate, not when you buy.Can my firm pay by invoice or sign an order form?Yes. An annual Reamer Server licence can be paid by invoice, issued by Paddle and payable within 14 days by bank transfer, and a signed order form is available on request. Both are at the same prices as the card checkout. The Reamer Server trial and the monthly Reamer Research subscription are card only.What counts as a seat? Can I move it to another machine?A seat is one product on one machine at a time, with unlimited runs and processes on that machine. To move it, deactivate on the old machine and activate on the new one. If the old machine is lost, support releases the seat by hand. A Reamer Research seat is also personal to one person.What happens when my licence expires?Anything already running keeps running. Expiry never stops a live process, including a Reamer Server instance that is trading. What it stops is starting a new process, so after expiry a restart will fail until you renew. A Reamer Research subscription renews each month on the same key until you cancel; a Reamer Server licence never renews or charges automatically, and renewing it is a new purchase.Can I get a refund?Refunds are handled by Paddle, the merchant of record that sells every Reamer Labs licence, under Paddle's refund policy. A request goes to Paddle within 14 days of purchase, and Paddle decides it case by case. There is no partial refund partway through a term; cancelling a Reamer Research subscription stops the next monthly charge. A $20 month of Reamer Research, or the paid Reamer Server trial, is where you decide whether the product fits, and much of it can be checked for free before that.What support is included?Email support from the person who builds the product, included with every active licence and not sold separately. Hours are 09:00 to 18:00 India time on weekdays, and requests are triaged into three severity tiers with best-effort acknowledgment targets of one, two and five business days. There is no 24/7 desk, no phone line and no contractual SLA unless a signed order form commits one.What exactly do I receive after buying?An email with your licence key and a link to download the kit. The kit is the product itself, compiled libraries, ready-to-run Python, C++ and Go code in source, command-line tools and the full documentation, and it holds no key. You activate the key once per machine with the reamer-license tool, and the term starts then. Nothing is shipped physically and nothing is hosted for you.
Buy a licenceKey and kit by email on payment.