Eventador for Data Science | Eventador | The Streaming Data Engine for Killer Applications

Eventador for Data Science

Learn how the Eventador Platform is a breakthrough for building data science pipelines

Want to learn more about how Eventador can help Data Science teams?



Key Features


High-velocity data can be challenging to use in your projects and analysis. Eventador was built to solve this problem. It’s easy to process and prepare data for use with a powerful processing paradigm that’s easy to use via Structured Query Language (SQL).

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.

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Create Input Transforms

Messy and inconsistent data can be a pain. Create input transforms with a few lines of Javascript to mutate your data upstream of any schema definition. You can read headers, normalize data, add logic, and filter out bogus or non-standardized data.

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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.

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Self-service SQL For the Win

Declaratively request the data you are actually looking for. Aggregate, filter, mutate, and join data using ANSI standard SQL. Create jobs to run these queries continuously from source to destination. Queries are evaluated using a real-time parser, so you get instant feedback and can iterate on creating the SQL that gives you the data you need. Use user defined functions (UDFs) in Javascript to add further processing logic or enrich data on the fly.

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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.

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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.

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