Build a Snowflake Data Lake or Data Warehouse.

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Integrate data in real-time on your Snowflake data lake while reducing Snowflake compute costs drastically

The case for building a Data Lake on your Snowflake Data Warehouse

A single repository for all your raw data is a compelling proposition. The Snowflake Data Lake 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.

Get ready-to-use data to your Snowflake Data Lake without coding

BryteFlow makes data accessible on 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.

Check out BryteFlow’s data integration on Snowflake
How to load terabytes of data to Snowflake fast
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Loading data to the Snowflake Data Warehouse

Set up your Snowflake Data Lake in one day.

BryteFlow’s automated Snowflake ETL process makes data integration a breeze.

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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.

Save on Snowflake data costs

BryteFlow data replication uses very low compute so you can reduce Snowflake data costs.

Upload data fast to the Snowflake Data Warehouse

BryteFlow meshes tightly with Snowflake to provide automated, fast data integration, in real-time. Here’s what you can do with BryteFlow on your Snowflake data lake or data warehouse. Get a Free Trial of BryteFlow

Change Data Capture your data to the Snowflake data warehouse with history of every transaction

BryteFlow continually replicates data to the Snowflake data lake in real-time, with history intact, through log based Change Data Capture. BryteFlow Ingest leverages the columnar Snowflake database by capturing only the deltas (changes in data) to Snowflake keeping data in the Snowflake data warehouse synced with data at source.

Data is ready to use – Get data to dashboard in minutes

BryteFlow Ingest on the Snowflake data warehouse provides a range of data conversions out of the box including Typecasting and GUID data type conversion to ensure that your data is ready for analytical consumption or for Machine Learning purposes.

Transfer data with speed and performance to Snowflake

BryteFlow Ingest uses fast log-based CDC to replicate your data to the Snowflake data warehouse. Data is transferred to the Snowflake data lake at high speeds in manageable chunks using compression and smart partitioning.
How to load terabytes of data to Snowflake fast

Automated DDL and performance tuning in the AWS-Snowflake environment

BryteFlow helps you tune performance on the AWS-Snowflake environment by automating DDL (Data Definition Language) which is a subset of SQL.

BryteFlow offers flexibility for data preparation

You have the choice of transforming and retaining data on AWS S3 and pushing it selectively to Snowflake data warehouse – for multiple use cases including Analytics and Machine Learning. Or replicating and transforming data directly on the Snowflake data lake itself.

Make Snowflake’s performance faster by preparing data on the AWS S3 data lake

BryteFlow frees up the resources of the Snowflake data warehouse by preparing your data on Amazon S3 and only pushing the data you need for querying onto Snowflake.

Use AWS S3 for storage and boost Snowflake cluster performance

You can choose to save all your data on Amazon S3 where typically storage costs are much lower. On the Snowflake data warehouse you need to only pay for the resources you actually use for the compute – this can translate to a large savings on data costs. This also enhances the performance of the Snowflake cluster.

Automated Data Reconciliation on the Snowflake data warehouse

You are assured of getting high quality, reconciled data always with BryteFlow TruData, our data reconciliation tool. BryteFlow TruData continually reconciles data in your Snowflake data lake or data warehouse with data at source. It can automatically serve up flexible comparisons and match datasets of source and destination.

Ingest large volumes of data automatically to your Snowflake database with BryteFlow XL Ingest

If you have huge petabytes of data to replicate to your Snowflake data lake or data warehouse, BryteFlow XL Ingest can do it automatically at high speed in a few clicks. BryteFlow XL Ingest is used for the initial full ingest in case of very large datasets. It uses smart partitioning and parallel sync with multi-thread loading to load bulk data fast.

Dashboard to monitor data ingestion and data transformation instances on the Snowflake data warehouse

Stay on top of your data ingestion and data transformationto the Snowflake data lake or data warehouse with the BryteFlow ControlRoom. It displays the status of BryteFlow Ingest and BryteFlow Blend instances displaying latency, operation start time, operation end time, volume of data ingested, transformation jobs etc.

Data transformation with data from any database, incremental files or APIs

BryteFlow Blend our data transformation tool enables you to merge and transform data from virtually any source including any database, any flat file or any API for querying on your Snowflake data lake or data warehouse.

No-code, automated data migration from Teradata and Netezza to the Snowflake data warehouse

BryteFlow can migrate your data from data warehouses like Teradata and Netezza to your Snowflake data warehouse without coding. BryteFlow automatically creates your tables on Snowflake – no coding needed.

Get built-in resiliency for data integration on Snowflake

BryteFlow has an automatic network catch-up mode. It just resumes where it left off in case of power outages or system shutdowns when normal conditions are restored. This is ideal for Snowflake’s big data environment which routinely handles data ingestion and preparation of thousands of petabytes of data.

 

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 Ingest: our data replication tool

This data replication tool extracts and replicates data from any file, database or API to your Snowflake data warehouse.
About BryteFlow Ingest 

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.

Read: How to load terabytes of data to the Snowflake data warehouse fast