It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake, Firebolt Data Warehouses Amazon S3 Data Lakes and MySQL, MongoDB, TokuDB, DynamoDB, PostgreSQL databases to name a few. Connectors: Hevo supports 100+ integrations to SaaS platforms, files, databases, analytics, and BI tools.These can be configured and tested before putting them to use. Hevo also offers drag and drop transformations like Date and Control Functions, JSON, and Event Manipulation to name a few. You need to edit the event object’s properties received in the transform method as a parameter to carry out the transformation.
It also allows you to run transformation code for each event in the Data Pipelines you set up. Transformations: Hevo provides preload transformations through Python code.Completely Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.Its strong integration with umpteenth sources allows users to bring in data of different kinds in a smooth fashion without having to code a single line.Ĭheck out some of the cool features of Hevo: Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance.
In the next section, we will be discussing Snowflake vs Firebolt to know the key differences between the two cloud storages.Ī fully managed No-code Data Pipeline platform like Hevo Data helps you integrate and load data from 100+ different sources (Including 40+ Free Data Sources) to a destination of your choice such as Snowflake and Firebolt in real-time in an effortless manner. You can also scale your storage depending on your storage needs. The Snowflake Data Warehouse provides security and protection of data using Amazon S3 policy controls, SSO, Azure SAS tokens, and Google Cloud Storage access permissions. Its data architecture uses the scalable, elastic Azure Blobs Storage as the internal storage engine and Azure Data Lake to store the Unstructured, Structured, and On-premise data ingested via the Azure Data Factory. Snowflake refers to a Data warehouse-as-a-Service (DaaS) platform developed for the Cloud. It turns all impossible data problems into easy everyday tasks. If you need to make changes to your Schema frequently, make your Semi-Structured data ready for analytics, or your queries are too slow even after optimizing them, choose the Firebolt Data Warehouse. It is suitable for aggregating data that lacks granularity. Note that there are no impossible data challenges with the Firebolt Database. It is 4-6000x faster than other Cloud Data Warehouse providers like Snowflake, Athena, Amazon Redshift, and others. The Firebolt Data Warehouse comes with all that you need to give your users an unbelievable data experience. It was developed for AWS with a powerful SQL query engine that separates computes and storage, enabling users to spin up many isolated resources on a similar database.īusinesses that use Firebolt’s Data Warehouses, deliver Petabyte-scale High-Performance and Interactive Analytics in a matter of weeks, enabling employees and analysts to analyze huge volumes of data and improve the ROI for data collection. It offers Fast Query Performance and combines Elasticity, Simplicity, Low cost of the Cloud, and Innovation in Analytics.
Firebolt vs Snowflake: Handling Semi-Structured Data.