Building blocks for a modern financial data platform.

Building a modern data platform shouldn't be painful. Our battle-tested components help you get started quickly. Begin building your platform today.

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Fabrik

One-Line. Tremendous Power.



Access. Retrieve your time series data using a an intuitive query layer using your favorite language.

Temporal. Request truly point-in-time data, use three time dimensions, get back clean and standardized data.


import pandas as pd

from pyfabrik.client import FabrikClient
from pyfabrik.models import FabrikReadRequest \
     FabrikReadResponse, FabrikWriteRequest

client = FabrikClient()

query: str = """
indicator:i[series='LF2G']
ons.macro[series,value]
e 2000-01-01 2020-02-01 q v 2000-01-01 2020-02-01 q k 2021-04-21
"""

r: FabrikReadRequest = FabrikReadRequest(
    definition=query,
    warehouse="snowflake"
)

res: FabrikReadResponse = client.read(r)
df: pd.DataFrame = res.df

df.head(10)
...

Bakplane

Provision, Evolve, and Decouple.



Independence. Provides vendor independence across: engines, datasets, warehouses, and landing-zones.

Centralized. All your platform coordinated from a central command and control center.


# Bootstrap your platform
bp landingzone apply -f s3.json
bp engine execution apply -f aws_emr.json
bp warehouse apply -f snowflake.json
bp ontology apply -f investment.json
bp adapter apply -f ons.json

# Ingest data
bp ingestion session create -a ons -l s3 -e dominus -w snowflake
bp ingestion session execute 1 -e aws_emr
bp ingestion session publish --all-resources -d snowflake 1

# View Data
bp resource preview -c ons_series -w snowflake
...

FinFlo

Turn-key Adapters. Machine Readable.



Note: The data must be in your posession, and you must be licensed to use this data. Our adapters simply manipulate existing data in your platform. We do not have access to data, nor we have a SaaS offering.

Ingestion. Over 100+ ready-to-use scalable data adapters for a variety of financial datasets.

Artifacts. Extract time-variant entities, relationships, and assets, into a machine readable format.


from finflo import Emitter

emitter = Emitter.from_env()

emitter.emit(Asset(
  resource_code="ons_series",
  fields={
      "series": data_point.series,
      "dataset": data_point.dataset,
      "units": data_point.unit,
      "value": data_point.value,
      "frequency": data_point.frequency,
  },
  effective_start_dt=data_point.effective_start_dt,
  effective_end_dt=data_point.effective_end_dt,
  valid_start_dt=data_point.valid_start_dt,
  valid_end_dt=data_point.valid_end_dt
))
...

Dominus

Master data management. Reenvisioned.



First-Class. Your entity data, matched perfectly, explored by point in time traversal or entity resolution.

Quality. Increase usable entity universe by detecting anomalies, conflicts, coverage gaps, and dubious data, measuring, and applying automated/by-hand overrides.










r = client.ResolveEntity(
    ResolveEntityRequest(
        entity_type_code="economic_indicator",
        descriptors=[
            Descriptor(
                attribute_code="ons_id",
                value="JOF2",
            ),
        ],
        effective_dating=("1995-1-1", "2020-12-31")
    )
)
...

Turbo-charge your initiative with instantly available modules.

Building a modern data platform requires solving various problems, ranging from data ingestion, warehouse publishing, data quality checks and of course security mastering.

Adapters

Create data adapters that extract data from a variety of sources with blazing speeds.

Ontology

Create rich data models with hundreds of entities and relationships, empowering complex temporal graph traversals.

Warehouse

Store your shaped data in any data warehouse of your choice, with built-in support for Snowflake, RedShift, BigQuery, Postgres, MSSQL and MySQL.

Dialects

Define and implement domain specific languages for accessing your data, exactly how you want to describe accessing it.

Resource

Persist your own data, to be queried in addition to data provided by vendors, without losing any of the temporality benefifts.

Entities

Represent real world entities as first class citizens of the system.

Landing Zone

Persist your critical unstaged data in modern, scalable object stores, including Amazon S3, Google Cloud Storage and Azure Blob Store.

Execution Engines

Execute your adapters and applications in different execution engines. Built-in support for Kubernetes, AWS Lambda, AWS EMR, Google Dataflow, Google Cloud Run, and more.

Mastering Engines

Master your entities data, and build a rich and temporal view of all your entities in a centralized location.

Your Tools

Game Changing

Learn about the core components, and how they operate seamlessly together, helping you to maximize 99.999% of your data.




By the numbers

Build your platform.

We've made it 10x easier for financial users to integrate all kinds of data into their applications, workflows, analytics, and models.

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Integrations

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API Endpoints

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Languages

Forward thinking

Schedule a demo in 3 days flat.

Design the demo you'd like to see, one that is custom-fit for you, we'll do it within 3 days, and your whole team is invited.