Data Processing

Traditional ETL solutions are still quite powerful when it comes to:

• Common connectors with small-medium data volumes : we still have a lot of respect for companies like Fivetran, who have really nailed the user experience for the most common ETL use cases, like syncing Zendesk tickets or a production Postgres read replica into Snowflake. The only

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Magika

Magika is a novel AI powered file type detection tool that relies on the recent advance of deep learning to provide accurate detection. Under the hood, Magika employs a custom, highly optimized Keras model that only weighs about 1MB, and enables precise file identification within milliseconds, even when running on a single CPU.

In an evaluati... See more

What is Hatchet?

Hatchet replaces difficult to manage legacy queues or pub/sub systems so you can design durable workloads that recover from failure and solve for problems like concurrency , fairness , and rate limiting . Instead of managing your own task queue or pub/sub system, you can use Hatchet to distribute your functions between a set of wor... See more

Optimizing Further

Creating so many indices and aggregating so many tables is sub-optimal. To optimize this, we employ materialized views, which create a separate disk-based entity and hence support indexing. The only downside is that we have to keep it updated.

CREATE MATERIALIZED VIEW search_view AS

ᅠᅠSELECT c.name FROM company c UNION

ᅠᅠSELECT c.na... See more

So what abstractions do we have as of today? For example, let’s take the resource abstraction (Dagster, Prefect, referred to as an operator in Airflow). You abstract complex environments and connections away with a simple construct like that. You have the immediate benefits of defining that once and using it in every task or pipeline with context.r... See more

Spice.ai OSS

What is Spice?

Spice is a small, portable runtime that provides developers with a unified SQL query interface to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake.

Spice makes it easy to build data-driven and data-intensive applications by streamlining the use of data and mach... See more

DataTrove

DataTrove is a library to process, filter and deduplicate text data at a very large scale. It provides a set of prebuilt commonly used processing blocks with a framework to easily add custom functionality.

DataTrove processing pipelines are platform-agnostic, running out of the box locally or on a slurm cluster. Its (relatively) low memory... See more

Clean & curate your data with LLMs

databonsai is a Python library that uses LLMs to perform data cleaning tasks.

Features

• Suite of tools for data processing using LLMs including categorization, transformation, and extraction


• Validation of LLM outputs


• Batch processing for token savings


• Retry logic with exponential backoff for handling rate limits an

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Overview¶

Ballista is a distributed compute platform primarily implemented in Rust, and powered by Apache Arrow.

Ballista has a scheduler and an executor process that are standard Rust executables and can be executed directly, but Dockerfiles are provided to build images for use in containerized environments, such as Docker, Docker Compose, and Kube... See more