tolerantsoftware/match repository overview

⁠Quick reference

• Maintained by: https://www.tolerant-software.de/⁠
• Where to get help: [email protected]⁠
• Release Notes: https://www.tolerant-software.de/en/products/tolerant-match/product-support/⁠
• All Configurations and further documentation to use this image orchestrated with other images for the complete Match Experience can be found in our GitHub: https://github.com/tolerantsoftware/match⁠

⁠Supported tags and respective Documentation links

• 11⁠
• 12.0⁠
• 12.1⁠

⁠Product Overview

⁠Duplicate matching, data cleansing and address cleansing for address lists and customer data

Well-maintained address lists and customer master data are the basis for successful marketing and sales campaigns. In addition, an error-free address database is crucial for meaningful analyses and statistics. This is the only way to make operational and analytical decisions that drive your business forward. Therefore, it is important to perform a duplicate check on a regular basis to find duplicates and clean up addresses. With TL Match you can find these duplicates in an automated, accurate and error-tolerant way.

⁠Fast and error-tolerant search

TL Match finds address data, products and customers quickly and accurately even in large data sets and even if only fragmentary information is available. The special technology in TL Match also allows you to combine different search options.

⁠Merge customer data from different sources in a clean and error-tolerant way

Legal requirements for data protection make it increasingly difficult to use external data sources for customer data. This makes it all the more important to maintain the high data quality of your own address databases. Addresses must be correct: Only if your customer data is clean can you utilise and deploy it effectively. But the volume of data is inevitably growing. And often customer data has to be maintained and matched in different systems or databases in parallel. With TL Match you can easily merge data from different sources without duplicates.

⁠Accurately find duplicates with TL Match

TL Match finds what belongs together. The easy-to-use software works accurately and error-tolerantly. Powerful search algorithms find data records that match already during data entry, but also during subsequent address cleansing or matching from multiple sources. TL Match’s error-tolerant search takes into account spelling or typing errors in names and addresses as well as different spellings. In addition, you can adapt TL Match to your needs and requirements at any time. For best results, clean data and duplicate-free address databases.

Some examples

⁠TOLERANT Match image

⁠Usage

Notes

⁠Starting

The services can be started using the following commands:

Without security:

docker compose up -d

With enabled security:

docker compose -f compose-secure.yml up -d

The docker compose command should be executed from the directory containing the compose.yaml or compose-secure.yml file.

⁠Stopping

The running services can be stopped using the following commands:

Without security:

docker compose down

With enabled security:

docker compose -f compose-secure.yml down

⁠Starting a batch process

A batch process can be stated with the following example

docker compose -f compose-batch.yml up -d

Removing the container after it has exited

docker compose -f compose-batch.yml down

Steps to use your own configuration and data for a batch process

• mount your configuration and data to the batch container
• adjust the entry point of the compose-batch.yml to match the following pattern:

entrypoint: ["matchBatch.sh", "<configFilename>", "<projectId>"]

⁠Starting an initial load process

An initial load process can be started using the following command:

Without security:

docker compose exec backend service.sh --endpoint operations --function stop.project --parameter projectId=<projectId>
docker compose exec backend matchInitialLoad.sh [-delete-backlog|-keep-backlog] <configFilename> <projectId>
docker compose exec backend service.sh --endpoint operations --function start.project --parameter projectId=<projectId>

With enabled security:

docker compose -f compose-secure.yml exec backend service.sh --endpoint operations --function stop.project --parameter projectId=<projectId>
docker compose -f compose-secure.yml exec backend matchInitialLoad.sh [-delete-backlog|-keep-backlog] <configFilename> <projectId>
docker compose -f compose-secure.yml exec backend service.sh --endpoint operations --function start.project --parameter projectId=<projectId>

The initial load example can be started using the following command:

docker compose exec backend service.sh --endpoint operations --function stop.project --parameter projectId=matchProject-1
docker compose exec backend matchInitialLoad.sh [-delete-backlog|-keep-backlog] config/matchserviceconfig.xml matchProject-1
docker compose exec backend service.sh --endpoint operations --function start.project --parameter projectId=matchProject-1

⁠Match as a cluster

A Match cluster can be started with the following command:

docker compose -f compose-cluster.yml up -d 

The docker compose command should be executed from the directory containing the compose-cluster.yml file, otherwise use the -f parameter for specifying the filepath.

A Match cluster can be stopped with the following command:

docker compose -f compose-cluster.yml down

The docker compose command should be executed from the directory containing the compose-cluster.yml file, otherwise use the -f parameter for specifying the filepath.

⁠Match in kubernetes (helm chart)

Match can be used in a kubernetes setup for zero Downtime and Redundancy purposes.

For more information and examples refer to our GitHub repository Match GitHub⁠

⁠License

TOLERANT Match is licensed under a commercial license. This means that the software can only be used for commercial purposes, and that the user must have a valid license to use the software. To get a valid license, please contact [email protected]⁠