Summarize this article with:
Trusted by data-driven companies
Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say
Andre Exner
"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."
Chase Zieman
“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
Begin by exporting the data from PersistIQ. Log in to your PersistIQ account and navigate to the section where your data is stored””usually in the form of lists or campaigns. Use the export function, typically available as a CSV file, to download your data to your local machine. Ensure all relevant fields are included in the export.
Once you have your CSV file, open it using a spreadsheet program like Microsoft Excel or Google Sheets. Review the data to ensure all the necessary fields are included and clean up any inconsistencies or errors. Consider renaming columns to match the field names you plan to use in Typesense for easier mapping later.
If you haven't already, install Typesense on your server. Typesense is a fast, open-source search engine that can be installed using Docker, Homebrew, or directly from the binary. Follow the official Typesense installation guide for your operating system to set up and run the Typesense server.
Define a collection schema in Typesense that matches the structure of your data from PersistIQ. Use the Typesense API or the Typesense Dashboard to create a new collection. Specify the fields (attributes) in your schema and set the appropriate data types for each field. Consider setting up fields for text search, faceting, and sorting.
Convert your cleaned and prepared CSV data to JSON format, which is required by Typesense. You can use a scripting language like Python to automate this conversion. Write a script that reads the CSV file and outputs each row as a JSON object, matching the schema you created in Typesense.
Use the Typesense API to bulk import your JSON data. For efficiency, batch your JSON objects into smaller groups if you have a large dataset. Send these batches to the Typesense server using the `/documents/import` endpoint. Ensure that your API requests are correctly authenticated and that the data is being imported into the correct collection.
After importing the data, verify that all records have been successfully added to Typesense. Use the Typesense Dashboard or API to query the collection and check for data integrity. Perform a few search queries to test the index's performance and accuracy, ensuring the data is correctly searchable and meets your requirements. Adjust the schema or re-import data if necessary.
By following these steps, you can manually transfer your data from PersistIQ to Typesense, leveraging direct data handling and API interactions without relying on third-party connectors.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
PersistIQ is a wonderfully lean software that makes sales outreach swift and easy. PersistIQ is a sales intelligence solution. The solution integrates with Salesforce as well as marketing automation platforms. PersistIQ is a salesforce automation software that assists sales teams in improving outbound sales. We've been able to deliver on the promise of many sales tools through PersistIQ, but rarely deliver the technology that actually helps you work more efficiently and sell more effectively.
PersistIQ's API provides access to a variety of data related to sales and marketing activities. The following are the categories of data that can be accessed through the API:
1. Contacts: The API provides access to contact information such as name, email address, phone number, job title, and company name.
2. Activities: The API allows users to retrieve data related to sales and marketing activities such as emails sent, calls made, and meetings scheduled.
3. Campaigns: The API provides access to data related to marketing campaigns such as email campaigns, social media campaigns, and advertising campaigns.
4. Leads: The API allows users to retrieve data related to leads such as lead source, lead status, and lead score.
5. Opportunities: The API provides access to data related to sales opportunities such as deal size, stage, and probability of closing.
6. Analytics: The API allows users to retrieve data related to sales and marketing performance such as open rates, click-through rates, and conversion rates.
Overall, PersistIQ's API provides a comprehensive set of data that can be used to optimize sales and marketing activities and improve overall business performance.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
