Receive the data
Connect sources, track delivery, recover missed updates and load history.
01 / 07Rayforce Cloud · Service proposal
A research workspace
with market data
already connected.
Choose the sources you need, add your own data and run queries or reusable analyses.
The proposed service covers data delivery, preparation and a managed Rayforce environment — the work needed before a dataset can support research.
Available in one workspace
01
Connected market data
Selected sources, history and maintained updates.
02
Your data and research
Positions, executions, custom queries and calculations.
03
Results you can use
Tables, recurring analyses and access through an API.
For quantitative research and portfolio analytics
02 / 07The client’s problem
A data subscription is the beginning of the work.
Before a team can answer a research question, someone has to make the data usable and keep the environment running.
Make it consistent
Parse formats, align identifiers and timestamps, validate fields and apply corrections.
Keep it queryable
Operate storage and compute, maintain datasets and run recurring workloads.
The proposed service takes care of
The agreed data pipeline and Rayforce environment.
The research team controls
The questions, calculations and use of the results.
The intended benefit is less recurring data and infrastructure work inside the client’s team.
03 / 07What the client gets
An environment the team can work in.
Connected datasets, managed compute and storage, and control over the analysis.
01 Create a workspace
A managed Rayforce environment for the team’s data and analytical workloads.
02 Connect datasets
Review coverage, history and update frequency. Connect entitled market datasets and add internal data.
03 Run an analysis
Write custom queries or use maintained analysis templates. Access results through the workspace or API.
Client workspaceProposed experience
Market datasets
Optional data services
Client data
Positions and internal tables
CoverageHistoryUpdate status
↓
Rayforce engine
Queries across connected and client datasets
Custom queries
Analysis templates
Results in the workspace and via API
04 / 07A concrete workflow
“Which instruments have unusual volume this morning?”
A reusable analysis over connected trade history, with the universe and comparison window chosen by the client.
1. Select the inputs
Trades or volume bars, session calendars and the client’s instrument list.
2. Run the calculation
Compare volume up to 10:00 with the average for the same session interval over the previous 20 sessions.
3. Work with the result
Inspect the ranked table, change the parameters or reuse the calculation through the API.
Illustrative output
20-session baselineRelative volume · 10:00
InstrumentVolume / baseline
Instrument A
2.4×
Instrument B
1.8×
Instrument C
1.2×
The result would include source timestamps and coverage status.
Example values for presentation purposes.
05 / 07The technology behind the service
Rayforce is the engine inside the workspace.
The existing Rayforce engine combines columnar analytics and graph operations in a shared query plan.
Tabular analytics
Filters, joins, aggregations and window functions over structured data.
Relationship analysis
Graph traversal and algorithms for connected entities, such as instruments, funds and issuers.
Programmatic access
Rayfall for queries and a C API for embedding. The engine can also be used independently of the proposed cloud service.
Execution modelRayforce engine
Tables
Prices, trades, positions
Relationships
Instruments, funds, issuers
Shared query plan
Tabular and graph operations
↓
Execution
Compute over the selected data
↓
Tables, aggregates and relationship results
06 / 07Market data integration
From a subscribed source to a queryable dataset.
Data providers and delivery partners connect at the ingestion layer. Preparation makes their data usable inside the client’s Rayforce workspace.
External sources and delivery
Integration into Rayforce Cloud
01 / Sources
Market data
Prices and trades
Reference data
Fund holdings
Client datasets
→
02 / Delivery
Data connection
Source connectivity
Acquisition
Delivery monitoring
Updates and backfills
→
03 / Ingestion
Data preparation
Parsing and validation
Schema mapping
Identifier alignment
Correction handling
→
04 / Workspace
Rayforce Cloud
Tables and history
Queries and joins
Analytical calculations
Client access / API
Integration boundary
A delivery connector feeds the ingestion layer, which publishes prepared datasets to a client workspace.
Source-specific delivery
Files, APIs or streams can be considered according to the source. Each requires an appropriate connector and update policy.
Provider-independent design
The delivery layer could be supplied by a data partner or connected directly. Data access follows the client’s entitlements.
07 / 07The proposed offer
A workspace and data services for the team’s research.
The core service
A Rayforce environment
Managed compute, storage, query execution and client access. The team can bring its own datasets.
Optional data services
Maintained market datasets
Agreed sources, historical coverage, update frequency and correction handling, delivered through provider integrations.
The analytical layer
Queries and reusable analyses
Custom research alongside maintained templates, with results available in the workspace and through an API.
The client receives
A working analytical environment with agreed datasets and operating responsibilities, ready for the team’s research workflows.
Defined for each setup
Data coverage and entitlements · history and update frequency · compute and storage · required analyses · support responsibilities
Rayforce is available today. Cloud and data services are the proposed offering.rayforcedb.com