Replicate data in real-time to your Snowflake Data Lake. Reduce Snowflake compute costs.
The case for building a Data Lake on Snowflake AWS or Snowflake Azure
A single repository for all your raw data is a compelling proposition. The Snowflake Data Lake whether on AWS or Azure, can be used to store data from all your disparate sources and create real-time dashboards to report on the data quickly or run analytics to uncover fresh insights. How to decide between a Date Lake vs Data Warehouse
Replicate in real-time and get ready-to-use data to your Snowflake Data Lake without coding
BryteFlow replicates data to your Snowflake Data Lake in real-time, without coding. BryteFlow is a completely automated data replication tool and does this in a couple of ways:
Directly: It replicates data from transactional sources to the Snowflake data warehouse in real-time using proprietary log-based Change Data Capture technology, it merges and transforms data automatically, making it ready for use instantly.
Indirectly: It loads data from the sources in real-time to Amazon S3 in ready-to-use formats like Parquet, ORC etc., transforms the data if required and then loads it to the Snowflake data warehouse for analytics.
BryteFlow uses enterprise log-based change data capture on legacy databases like Oracle, SQL Server, SAP, MySQL and more, and from applications like Salesforce etc. to move data from the sources to the Snowflake data warehouse in real-time. It maintains a replica of the source structures in Snowflake and merges the initial and delta loads automatically with SCD type 2 history if required.
Loading data into Snowflake Data Warehouse
Set up your Snowflake Data Lake in one day.
BryteFlow’s automated Snowflake ETL process makes data integration a breeze.
We offer complete support on your free trial including screen sharing, online support and consultation.
Are you looking to set up your Snowflake Data Lake fast? Or possibly you already have one and are looking for data migration to Snowflake? BryteFlow represents the easiest and fastest route to Snowflake.
No-code, self-serve data migration to the Snowflake data warehouse with our automated data replication tools for Snowflake
When migrating data to Snowflake you need to have a data replication solution that will get you there with minimum effort and minimum time. BryteFlow Ingest is ideal for Snowflake ETL since it is a completely automated data replication tool for Snowflake and the AWS environment. After you configure your account on Snowflake, you can install BryteFlow and connect to sources with just a couple of clicks -you should be up and running in a day. Your tables are created automatically on Snowflake – no coding needed!
Bulk data ingestion? Upload data to Snowflake fast
If you have huge datasets to replicate, bulk ingestions to your Snowflake data lake or data warehouse are easy. BryteFlow XL Ingest uses smart partitioning, compression and multi-thread parallel loading to ingest petabytes of data in minutes.
How to load terabytes of data to the Snowflake data warehouse fast
Get reconciled data on you Snowflake data warehouse or data lake
No more worries about missing data or incomplete data – BryteFlow is the only data integration tool for Snowflake that offers built-in data reconciliation. BryteFlow Trudata reconciles data in the Snowflake data warehouse with data at source and alerts you if data is missing so you can rest easy.
Reduce Snowflake Compute Costs
BryteFlow uses the lowest compute when replicating data to Snowflake. It has best practices for Snowflake baked in and replicates data to Snowflake fast, capturing only incremental loads after the initial full ingest. You can deploy in one day and get delivery of data in less than 2 weeks. How to cut down Snowflake costs by 30%
Fast Data Ingestion to the Snowflake Data Warehouse
BryteFlow provides Snowflake replication in real-time without coding. Here’s what you can do with BryteFlow on your Snowflake data lake or data warehouse. Get a Free Trial of BryteFlow
BryteFlow’s ETL Tools for Snowflake
It is easier than ever to load, merge and transform data from multiple sources for your Snowflake data
warehouse in real-time with BryteFlow’s automated ETL tools.
Try out BryteFlow’s ETL tools for Snowflake free
BryteFlow XL Ingest for bulk loading to Snowflake
Uses smart partitioning, parallel multi-thread loading and compression to replicate extra large tables fast to your Snowflake data warehouse for fast initial ingests.
About BryteFlow XL Ingest
BryteFlow Blend: our data transformation tool
Merges data from different sources and prepares and transforms it for Analytics, Machine Learning etc. for the Snowflake data warehouse or data lake.
About BryteFlow Blend
BryteFlow Trudata: our data reconciliation tool
Reconciles data in the Snowflake data warehouse with your data at source. Checks completeness of data including Type2 and issues alerts if data is missing or incomplete.
About BryteFlow TruData
BryteFlow ControlRoom: our data monitoring tool
The Bryteflow ControlRoom is an operational dashboard that monitors all instances of BryteFlow Ingest and BryteFlow Blend, displaying the statuses of various replication and transform instances on the Snowflake data warehouse.
About BryteFlow ControlRoom
The advantages of creating a
Snowflake Data Lake
A Snowflake Data Lake provides the flexibility to store and use your data as you choose.
Raw data for Machine Learning and AI in your Snowflake data lake
Unlike a data warehouse which stores data in structured format, a Snowflake data lake has the ability to store tons of raw data that can be used successfully for Machine Learning and AI purposes. You can model the raw data the way you want using BryteFlow Blend with Apache Spark to build models for Machine Learning.
Storage costs are low on the Snowflake data lake
The Snowflake data lake allows you to store all of your data at a lower cost. You don’t have to sift through and discard data on account of your budget. You only pay for compute when you are loading or querying data.
The Snowflake data lake gets rid of your data silos
You are not restricted by formats on the Snowflake data lake. Data can be stored in its native form including structured and semi-structured data (JSON, CSV, tables, Parquet, ORC, etc.). All kinds of data types can be collected and stored.
A Snowflake data lake offers instant elasticity and unlimited scalability
Being in the cloud means you can dynamically scale up compute resources on the Snowflake data lake as per required without impacting running queries or even enable the resources to scale up automatically when there is heavy concurrency.
You can accommodate all your users on the Snowflake data lake
The Snowflake data lake supports heavy concurrency and a huge number of workloads. An unlimited number of users can query a single copy of data without any impact on performance.
Snowflake data is extremely secure
The Snowflake data warehouse automatically encrypts all data. Multi-factor authentication and granular access control is reassuring. The Snowflake cloud data warehouse uses third party certification and validation to make sure security standards are met. Access control auditing is available for everything including data objects and actions within your Snowflake data lake.
The Snowflake data lake is fully automated as is Bryteflow
Built-in monitoring, performance tuning and best practices are all accounted for, so you can focus on getting the most out of your data.
Using BryteFlow to replicate, merge and transform data on your Snowflake data lake or data warehouse makes for a seamless, fast performance and even faster access to insight.