4 simple steps for migrating to
Google BigQuery with zero coding

Google BigQuery
Google BigQuery integration Create connections between sources to amazon redshift

Create connections
between data sources and Google BigQuery

data warehouse Google BigQuery pipeline by selecting tables

Prepare a source to the Google BigQuery pipeline by selecting tables in bulk

Data Integration ETL

Assemble a workflow and schedule it to start the Google BigQuery migration process

share your data over api hub

Share your data
with third-party platforms
over API Hub

Data Management

Simple and Intuitive

Switch to Google BigQuery like a boss

Data Connectivity

High-Speed Performance

Enjoy Google BigQuery high-speed performance with codeless data environment

Real-time Data Processing

Prebuilt Transformation

Say goodbye to tedious manual tasks with prebuilt transformation templates

Data Analytics

Monitoring Data

Monitor your Google BigQuery data frequently

Lyftrondata process

Hear how Lyftrondata helped accelerate the data
journey of MOL Group

New applications

ETL Lyftrondata enables instant analytics on WNI weather data that helped us streamline shipping lines. ELT

Data Analytics

Koichi Tsuji

Consulting Partner at MOL Group
Data Management


Google BigQuery Integration is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.

Integrations: Hadoop Integration is possible with Google BigQuery Integration tool.
Platform: Machine Scaling is feasible with Google BigQuery Driver.
Processing: Cloud Processing is accessible with the Google BigQuery Connectors tool.
Data Transformation: Real-Time Analytics is possible with BigQuery ETL.

Inappropriate for SMBs: Google BigQuery Integration is less appropriate to use in small businesses where data volume is low

Incapable IT resources: IT resources are not enough to maintain data quality with Google BigQuery Connectors tool.

Relational database issues: BigQuery ETL cannot be used to substitute a relational database.

Query running issues: Google BigQuery Driver is oriented on running analytical queries, not for simple CRUD operations and queries.

Start modernizing your Google BigQuery journey today

Google BigQuery journey