Eventador for Data Science
Learn how the Eventador Platform is a breakthrough for building data science pipelines
Stop Waiting for Data
Don't waste precious time waiting for queries to run or with maddening export times—especially against giant datasets or extremely high velocity feeds. Use Continuous SQL to continuously materialize data right into your notebooks and pandas.
Stop waiting and get back to the science.
Simplify Data Preparation
Wrangling data is frustrating and time consuming. Use SQL to filter, aggregate, clean, and join data from unstructured streams or static tables. And use user defined functions for more complex logic or define input transforms to normalize or obfuscate data.
Use powerful tools for wrangling data.
Achieve Data Feed Sanity
Create durable and named data API endpoints and bridge the divide between production data and historical data. Use these durable APIs instead of one-offs from the training and testing of models to production serving and monitoring.
Self-serve the data you need for models and computations.
Want to learn more about how Eventador can help Data Science teams?
Connect to Heterogeneous Data Sources
Whether it’s Apache Kafka, legacy databases, files, or logs, you can connect to your organization's data feeds where they live. No bulk import or synchronization required. Everything is a stream of data, including change data capture (Debezium) from ODS and system of record databases.
Create Input Transforms
Automatic Schema Inference
Automatically read JSON data to infer and build schemas. You don’t need to know anything about the data feed to start querying it in SQL. If you use Schema Registry with AVRO no problem either, it directly plugs into Eventador. Use complex and nested objects, unnesting and you aren’t required to flatten data.
Self-service SQL For the Win
High-performance Continuous SQL Engine
Utilize the Eventador Continuous SQL engine to create scalable, high-performance data processing jobs. Do it upstream of the database so your work, and you, don’t wait for slow queries. Because SQL is being continuously run on a stream of data, there is no need for indexes or a database at all. This unique architectural approach drastically increases performance and massively drops costs. Query results are presented as durable data APIs for direct use in your projects, computations, and models.
Curate Durable Data APIs
Data is materialized into curated, durable, and reusable REST data APIs. Analyze, train, test, and go production with clear access rules, normalized data, and simple access patterns for your favorite tools and frameworks like Python/Pandas, R, Julia, or any programming language or application that can read data via REST over SSL. Share the data APIs with your team, get DevOps buy-in, and deploy production. You can set retention times to keep data sets small, or go big.