Solving your ETL problems,
One question at a time

Before deciding on an ETL tool you need to define your data pipeline requirements. Learn more.

Event-driven ETL, also known as a data pipeline, differs from classic ETL in that they treat source data as a stream rather than pulling batches of data every (insert-interval-here). The first thing to consider is - do you need a data pipeline (event-driven ETL)?

Learn about the advantages Snowflake has over Amazon Redshift, including costs, database features, and maintenance.

Loading a CSV to Redshift is a pretty straightforward process, however some caveats do exist, especially when it comes to error-handling and keeping performance in mind. Learn more here.

There are a few ways to address this problem, and it mostly depends on what the requirements are: incremental dump and load, full dump & load, binlog replication, or a SaaS provider. Learn more.

ETL is the process of extracting data from a data store used for a certain task(s), and loading it to another data store to be used for some other task.

Striim is a real-time, streaming analytics and data integration platform. This allows analysis while data is “in-flight”.

Confluent is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream.

Learn about the two different ways to convert a database into a data warehouse.

Kafka allows you to think big, without compromising on the stability, reliability and the high performance of your system.

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