It's performance, superior features and unmatched functionality have led OneTick Database to be embraced by leading banks, brokerages, data vendors, exchanges, hedge funds, market makers and mutual funds.


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OneTick Time Series Database & Streaming Analytics Engine

The fastest and most advanced trade analytics platform.  

A Smarter Solution for Data Management

OneTick is the premier enterprise-wide solution for tick data capture, streaming analytics, data management and research. It captures, compresses, archives and provides uniform access to global historical data, up to and including the latest tick. OneTick has no limitations on data volumes, peak rates or length of stored history, and it collects every tick for all asset class types including equities, fixed income, futures, FX and options, as well as full order book data.

OneTick's powerful analytical tools enable clients to run historical simulations and back-tests, develop trading and market-making strategies, build transaction-cost models, perform real-time surveillance and answer regulatory compliance requirements. With its superior features and unmatched functionality, OneTick is being embraced enthusiastically by leading hedge funds, mutual funds, banks, brokerages, market makers, data vendors and exchanges.

Users can:

  • Access one integrated database for tick capture, retrieval and archiving
  • Connect directly to leading market data vendors through standard APIs
  • Leverage powerful analytics for quick data analysis
  • Reduce total cost of ownership by eliminating implementation and integration costs
  • Slash strategy time to production through an integrated data management system
  • Work with market data experts that understand your business


ADVANCED Analytics

OneTick is built from the ground up to understand market data. Its engine is finely-tuned to understand the nuances of trading, quoting and order book processing. We provide a broad set of in-built functions we call Event Processors focused on trading and quantitative research for tick data. While we are asset-class neutral, our library of analytical functions provides a means to research the relationship between trades and quotes, to instantly merge Order Books from multiple sources, to convert currencies for cross-border arbitrage and hundreds of other in-built functions expressly purposed for analysing markets. These analytics functions or Event Processors are easily amenable to other data such as executions, RFQ systems and user-definable content.



The Query Designer is a visual design tool enabling a user to graphically construct or model queries using a collection of query elements called Event Processors. Event Processors are nodes on a graph and can be linked in series or in parallel using a directed graph construct.  A query’s graph is assembled using a drag-n-drop, “paint a canvas” metaphor. Each Event Processor has its own unique parameter set. Parameter values can be simple static values, reference values (i.e. tick stream fields), evaluated conditions, or user-supplied input (e.g. aggregation interval) that can be supplied at query runtime.  


Our Python interface provides data scientists and quantitative researchers with the convenience of Python and the performance of OneTick.

Key Features:

  • Python interface used to create and run OneTick queries
  • Headless approach to development
  • Support for commonly used packages (i.e. Matplotlib, NumPy, Pandas and Jupyter notebooks)
  • Directly access OneTick’s Cloud and /or locally stored data

Machine Learning 

OneTick analytics have been extended to incorporate Machine Learning (ML) capabilities, using well-known open source ML libraries. Customers can use OneTick's machine learning event processors for training, prediction, performance evaluation, and real-time learning/prediction on-the-fly. These operations can be performed natively within OneTick, without having to export any data.

OneTick's ML algorithms address common machine learning categories such as classification, regression, and clustering. Specific algorithms include support vector machines, relevance vector machines, kernel ridge regression, and k-means clustering. The trained models are themselves stored as OneTick databases. 



OneTick’s proprietary time series database is a unified, multi-asset class platform that includes a fully integrated streaming analytics engine and built-in business logic to eliminate the need for multiple disparate systems.  The system provides the lowest total cost of ownership available. 


Combine querying and replaying of historical tick data with streaming analytics.  Publish real time analytics and signals. Query intraday and historical data with minimal latency.  Apply corporate actions with easy.


Handle complex order management and flow covering Order parent/child relationships, portfolio allocations, placements and executed trades of the order. Traverse through the life of an order with ease and drill down views into order flow organized by symbol, side, PM, trader, day, month or other time period


  • Multi-threaded 64-bit server architecture
  • No limitations on data volumes, peak rates or length of stored history.
  • Ability to handle all market data globally (over 10+ billion messages per day)
  • Bulk processing rate of more than 10 million ticks per second, per core
  • Real-time collection of 400K-600K messages per second, per core (depending on the data feed)
  • Each intraday loader can insert about 600K messages per second per core (depends on the normalization complexity)


  • Any number of collectors on any number of nodes
  • Any amount of storage accessible from the query engines (aka tick servers). Includes support for multiple file systems.
  • Multiple multi-threaded tick server processes on one physical server
  • Multiple physical tick servers each running 1+ tick server processes
  • Virtual databases and multiple real-time collector mounts


A wide range of features for the capture, management and analysis of financial data. Content-Aware for Trades, Quotes, Orderbooks, Executions across all asset classes. Support of both column and row store

  • High performance/high precision server-side analytics execution
  • Support for machine learning
  • Stitch history and real-time as one single data stream
  • Comprehensive Authentication/Authorization and data Entitlements


The OneTick platform can be fully deployed on-premise, fully hosted by OneMarketData on our private cloud (or public cloud) or a hybrid where a portion of the infrastructure is hosted/managed by OneMarketData and a portion is deployed on premise.

Elastic "burst" license fee models available for massive queries against hundreds or thousands of cores.


Visual Dashboard Designer

OneTick includes a dashboard designer that can be used to build new dashboards both for visualizing results of queries in historical or real-time CEP mode, and as control interfaces.  Visual Dashboards support historical and real-time CEP queries. OneTick Dashboards can run either as deployed Windows applications or as HTML5 web-based dashboards

The screenshot shows an example of the dashboard in design mode.

A drag-n-drop paradigm is used to add visualization and control elements to a new dashboard. Behind each display or control component (e.g. charts, tables) are one or more OneTick queries that connect to Tick Servers at the back end, which allows advanced functionality to be deployed quickly.  Dashboard components can also communicate by way of messages.

Real-time CEP dashboard displays continuously or with frequency predefined by the query parameters (for example, a real-time market monitor dashboard updates market-maker obligation metrics grids and charts), and can also examine historical data. At the back-end, the OneTick streaming analytics engine collects real-time market and transaction data and calculates the obligation metrics.


HTML5 web-based dashboard

In this application, user dashboards can be started any time. The latest calculated values and the recent history of calculated values will be available to dashboards immediately when they connect, and, from the user’s perspective, will update continuously on the dashboard thereafter.

Dashboard capabilities:

  • View real-time streaming or historical data using the same queries
  • Dynamic table sorting (tables can re-sort as data updates arrive)
  • Chart and table tabs can be torn off (desktop version)
  • Chart zooming
  • Flexible support for multiple time series in charts
  • High-capacity: capable of receiving high volumes of streaming data, and a million+ rows in tables.
  • Table filter header row

Real-time Alerts

Applications such as a real-time execution quality monitor can be configured to generate alerts on various conditions. These events can flow into an existing, configurable alert management workflow dashboard for reviewing, assigning, commenting on, and closing execution quality alerts.

This is a screenshot of an existing trade practice surveillance alert examination dashboard, which is an example of a specific configuration of the alerts-management component.




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