Happy holidays from all of your friends at Nexla. It’s been quite a busy 2021 for us and we’re excited for what 2022 has to bring. This will be the last Nexla Newsletter from us this year, so let’s dig in!
Nexla ? Firebolt: How-to?Data Mesh and Sub-Second Operational Analytics
We will be joining the Firebolt team for an upcoming webinar on January 11th to discuss and demonstrate how companies are embracing data mesh and sub-second analytics approaches. Register for the webinar today.
Product Updates
New Connectors: Databricks, Delta Lake, Teradata, and File Upload
This month we added several new connectors, check them out in Nexla: Databricks, Delta Lake, Teradata, and File Upload connector that let’s you upload and integrate files from your computer directly into your Nexla data flows.
Snappy Compression for Parquet Files
Working with Parquet files in Nexla just got an upgrade, with new Snappy compression available as an option for reading or writing files.
Oracle NetSuite Connector and Partnership
We’re proud to announce a new Oracle NetSuite connector. Now it’s easier than ever to bring NetSuite Analytics and Finances to be the preferred way to integrate data to and from Oracle services.
We’ve seen the API Economy, but now it’s time for the Data Economy because ultimately what matters is that data gets delivered securely, reliably, and in a timely way. Read the blog post.
Forbes Highlights Nexla’s Role in Solving Financial Software Challenges
In the News: Forbes recognizes how Nexla defines and enables automated data mapping—matching data fields across systems to reduce errors and fragmentation. By applying AI and machine learning to integration, Nexla helps make financial data flows more accurate and resilient.
In the News: Nexla CTO Amey Desai shares how Nexla supports MCP, enabling secure, AI-native data integration through Nexsets and agentic orchestration without compromising standards.
Data Variety: The Silent Killer of AI — And How to Conquer It
In the News: Nexla CEO Saket Saurabh explains how data variety—differences in formats, sources, and structures—is a major reason AI initiatives fail to scale. You’ll learn about modern strategies like virtual data products and agentic integration.