Rivery is a no-code ELT platform that enables rapid data ingestion, transformation, and orchestration from various sources into cloud data warehouses. It streamlines data workflows and reduces processing time, allowing businesses to efficiently manage their data operations and enhance analytics capabilities.
Funding
$30M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TGFounders
Product
Problem
Organizations struggle to efficiently extract, transform, and load data from disparate sources into cloud data warehouses, often relying on complex coding and multiple tools. This results in slow data delivery, increased costs, and difficulty in managing and scaling data operations.
Solution
Rivery offers a no-code ELT platform designed to simplify and accelerate data pipeline creation for analytics and AI applications. The platform enables users to ingest data from various sources, transform it using SQL or Python, orchestrate data flow with advanced scheduling and logic, and activate data by pushing it into their existing tech stack via reverse ETL. Rivery streamlines DataOps management by providing visibility into pipeline activity and consumption, allowing businesses to scale their data operations without infrastructure setbacks. The platform's pre-built starter kits and custom connection capabilities reduce development time and simplify the data integration process.
Target Audience
Rivery targets data leaders, data engineers, and data analysts who need to build, manage, and scale data pipelines for analytics and AI, as well as enterprises seeking to simplify their data stack and reduce data-related costs.
Features
- No-code interface for building end-to-end ELT data pipelines
- Pre-built connectors for databases, marketing platforms, CRM systems, and analytics tools
- Support for custom data integration through low-code connections
- Data transformation using SQL, Python, and pre-built data model kits
- Advanced data orchestration with conditional logic, containers, and loops
- Reverse ETL functionality to push data into operational systems
- Automated schema creation and incremental loads
- API and CLI for remote execution, deployment, and management of data pipelines
- Data Connector Agent to build data pipelines faster with GenAI