Technique
ETL
Extract, transform, load (ETL) is a three-phase process where data is extracted from the source, transformed and loaded into the destination. Etlworks supports any-to-any ETL. Most of the connectors in Etlworks can be used as a source as well as a destination.
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Documentation
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When to use
- When you need to ETL data from any source to any destination
- When you need to execute complex transformations
- When you need to process sources (files, databases tables) by a
wildcard
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Technique
ELT
Extract-Load-Transform (ELT) is a process, in which the
transformation step is moved to the end of the workflow, and data is
immediately loaded to a destination upon extraction.
Etlworks supports executing complex ELT scripts
directly in the target database, which greatly improves the
performance and reliability of the data ingestion.
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Documentation
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When to use
- When you need to efficiently transform data of any size or type
- When you need to process structured and unstructured big data
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Technique
Reverse ETL
Reverse ETL is the process of syncing data from a source of truth
like a data warehouse to a system of actions like CRM, advertising
platform, or other SaaS app to operationalize data. Etlworks
supports reverse ETL from
Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse
Analytics, Greenplum and any data warehouse built on top of the
relational database.
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Documentation
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When to use
- When you need to push data into more systems, getting better use of
your data
- When you need to continuously sync data between different systems
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Technique
Streaming data integration
Streaming data integration is the continuous collection,
in-stream processing, pipeline monitoring,
and real-time delivery of data.
Etlworks supports streaming data from and to messages queues,
CDC-enabled databases, MongoDB
and other data sources.
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Documentation
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When to use
- When you need to collect and analyze information in real-time
- When the collected information is constantly changing (for example
CDC stream)
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Technique
API integration
API integration is the connection between two or more applications
via their APIs that allow systems to exchange data sources. Etlworks
can connect to any REST, SOAP and GraphQL API.
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Documentation
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When to use
- When you need to collect data from the APIs
- When you need to send data to the third-party APIs
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Technique
Event-driven data integration
Event-driven data integrations are triggered by an event in one system, and they trigger a predefined corresponding event in another. Etlworks supports triggering data integration flows by inbound HTTP requests from third-party systems.
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Documentation
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When to use
- When you need to enrich data from multiple sources and expose it to
third-party systems
- When you need to ETL data sent by the third party system into any
destination
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Technique
Working with on-premise data
Etlworks uses Integration Agent to access on-premise applications
and databases. An Integration Agent is a zero-maintenance,
easy-to-configure, fully autonomous ETL engine which runs as a
background service behind the company's firewall. It can be
installed on Windows and Linux.
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Documentation
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When to use
- When you need to run data integration flows that require access to the on-premise data behind the firewall
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