Load data from Elasticsearch to Azure SQL in a few clicks
Focus on your business, not on getting your Elasticsearch data into Azure SQL. Build scalable, production-ready data pipelines and workflows in hours, not days.
Elasticsearch to Azure SQL Data Pipelines Made Easy
Your unified solution for building data pipelines and orchestrating workflows at scale.
How to set up a connection from Elasticsearch to Azure SQL
Elasticsearch & 190+ Other Data Connectors, Fully Managed For You
Connect easily to Elasticsearch with 100% compatibility, regular API updates, and a wide range of other pre-built data connectors out of the box.
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Start analyzing your Elasticsearch data in minutes with Rivery
Elasticsearch is a distributed, free and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. Known for its simple REST APIs, distributed nature, speed, and scalability, Elasticsearch is the central component of the Elastic Stack, a set of free and open tools for data ingestion, enrichment, storage, analysis, and visualization.
About Azure SQL
Microsoft Azure SQL Database is a managed cloud database provided as part of Microsoft Azure. Build apps that scale with the pace of your business with a managed and intelligent SQL database in the cloud.
Rivery's SaaS platform provides a unified solution for ingestion, transformation, orchestration, and data operations.
“We saved several $100K we could have spent on development and maintenance. Within a few hours, you can build a production-ready, scalable ETL system.”
Gal Bar, Founder and CEO
Data Process Automation
“We solved some of our most complex data challenges with Rivery. The ability to create a unified data pipeline that is always up-to-date has been a game changer.”
Tali Stern, Director of Business Intelligence
Link Any Data Source
“Rivery has more than delivered on the value proposition I sold my leadership on. Rather than hiring two more developers, I’ve been able to build all these pipelines on my own.”
Sean Lucas, Head of Data Engineering
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