From Ploomes to Redshift: managed, scheduled, no code.
Creating a pipeline that sends data from Ploomes to Redshift data warehouses takes only a few minutes with Kondado. And the whole integration from Ploomes to Redshift is managed and executed by our platform. With Kondado, you can focus on extracting value from Ploomes data and combining it with other data in your Redshift data warehouse
Kondado enables businesses to replicate their Ploomes CRM data directly into Amazon Redshift without writing code or managing complex API connections. Simply authenticate your Ploomes account as a data source, configure your Redshift cluster as the destination, and select which pipelines you want to replicate from the available 36 options. The platform handles the data extraction, transformation, and loading processes automatically on a configurable schedule that you control, whether you need updates every 5 minutes or once daily. Once your data arrives in Redshift, you can combine Ploomes sales information with other business data sources to build comprehensive analytics workflows and custom dashboards.
With Kondado, technical teams and analysts can centralize Ploomes CRM records, deal information, and client data into their Redshift data warehouse efficiently. This direct pipeline eliminates manual CSV exports and ensures your analytics environment always contains current information for reporting and business intelligence.
Kondado replicates 36 Ploomes pipelines containing 275 fields to Redshift on a configurable schedule ranging from every 5 minutes to daily, enabling near-real-time analytics of CRM, sales, and client management data.
Once your Ploomes data lands in Redshift, you can unlock powerful analytics by querying the Deals pipeline to analyze sales funnel progression and conversion rates across different stages. The Clients pipeline enables comprehensive customer segmentation analysis when joined with external marketing data, while the Products and Sales pipelines provide inventory and revenue insights for financial reporting. This centralized data foundation supports custom SQL queries and connects seamlessly to visualization tools like Power BI, Looker Studio, or Google Sheets for automated reporting workflows.
Try out all the features for free for 14 days
Replicated to Redshift
Ploomes data available for Redshift
Tables Kondado writes into your Redshift, on a schedule you control.
36
available pipelines
275
extractable fields
Redshift
Destination
Available integrations
Positions
Table contains information about positions, including id, name, and associated user profile.
Cities
Table presents data about cities, including id, name, and associated state.
Cities: states
Table provides information about states related to cities, including id and state name.
Cities: countries
Table contains data about countries associated with cities, including id and country name.
Clients (companies and individuals)
Table presents information about clients, including id, name, email, and status.
Clients: ratings
Table provides data about client ratings, including id and rating name.
Clients: sources
Table contains information about client sources, including id and source name.
Clients: relationships
Table presents data about relationships between clients, including id and relationship type.
Clients: segments
Table provides information about client segments, including id and segment name.
Clients: status
Table contains data about client status, including id and status description.
Client Types
Includes fields such as id and name, allowing categorization of clients into different types for better management.
Departments
Contains fields such as id and name, facilitating the organization and structuring of departments within the company.
Documents
Presents fields such as id and filename, allowing management of documents associated with clients and sales.
Currencies
Includes fields such as id and currency, essential for financial management and conversion of values in different currencies.
Deals
Has fields such as id, ordernumber, and amount, allowing tracking and analysis of completed sales.
Deal Stages
Includes fields such as id, name, and ordination, which help define the progression of deals through different stages.
Deal Funnels
Presents fields that allow visualization and management of different sales funnels and their stages.
Deal Loss Reasons
Includes fields such as id and name, helping to identify and analyze the reasons why deals were not closed.
Deal Status
Presents fields that indicate the current status of deals, allowing better tracking of progress.
Products
Contains fields such as id and name, essential for managing and categorizing the products offered.
Product Groups
Includes fields such as id, name, and description, allowing for the categorization of products into specific groups for better organization and analysis.
Product Families
Contains fields such as id, name, and group_id, facilitating the organization of products into related families for more efficient management.
Proposals
Presents fields such as id, filename, and approval status, allowing for the management and tracking of proposals sent to clients.
Proposal Products
Includes fields such as proposal_id, product_id, and quantity, detailing the products included in each proposal for accurate tracking.
Proposal Approval Status
Contains fields such as id and name, allowing for the categorization of different approval statuses for submitted proposals.
Interaction Records
Includes fields such as id, type, and date, recording interactions made with clients for relationship analysis.
Tasks
Presents fields such as id, name, and status, allowing for effective management of tasks assigned to users within the platform.
Task Recurrence Intervals
Contains fields such as id and frequency, defining the periodicity of tasks for better work organization.
Task Types
Includes fields such as id and name, categorizing tasks into different types for easier management.
Email Reminder Types
Presents fields such as id and description, allowing the configuration of different types of email reminders for users.
Users
Table contains information about users, including fields such as id, name, and email, as well as role id and profile id.
User Suspension Reasons
Table lists the reasons for user suspension, with fields such as id and name, along with comments on the suspension.
User Profiles
Table presents user profiles, including fields such as id, name, and avatar url, along with phone and user language.
Sales
Table contains data on sales, including fields such as id, order number, date, customer id, and total sale amount.
Sales Stages
Table lists sales stages, with fields such as id, name, icon, and ordination of stages within a funnel.
Sales Products
Table contains information on sold products, including fields such as order id, product id, and quantity, along with unit price and discount.
Sync data automatically — no code, no manual exports.
1
Connect Your Ploomes Account
Log into Kondado and add Ploomes as a data source by entering your API credentials to establish the initial connection. This authentication allows Kondado to access your CRM data and display the available 36 pipelines for replication.
2
Configure Redshift Destination
Enter your Amazon Redshift cluster connection details including host, database name, and credentials to establish the target location for your data. Kondado validates the connection to ensure your Ploomes data can flow directly into your data warehouse environment.
3
Select Pipelines and Schedule
Choose which of the 36 Ploomes pipelines to replicate, such as Deals, Clients, or Products, then set your update frequency from 5 minutes to daily. Once activated, Kondado automatically maintains your selected datasets in Redshift on the configured schedule.
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Answers about sending Ploomes data to Redshift automatically
How do I connect Ploomes to Redshift using Kondado?▼
Start by adding Ploomes as a data source in your Kondado account using your API credentials, then configure your Redshift cluster credentials as the destination. Select from 36 available pipelines including Deals, Clients, and Products, set your preferred update schedule, and Kondado begins replicating data automatically.
What Ploomes data can I replicate to Redshift?▼
Kondado offers 36 pipelines covering 275 fields from your Ploomes environment, including sales records, client information, deal stages, product catalogs, and user data. You can select specific pipelines such as Deals, Clients (companies and individuals), or Sales Products to replicate only the data relevant to your analytics needs.
How often does Ploomes data update in Redshift?▼
Kondado updates your Redshift destination on a configurable schedule that you control, with options ranging from every 5 minutes to daily intervals. This flexibility allows you to balance data freshness with processing costs, whether you need near-real-time sales tracking or daily consolidated reporting.
What format does Ploomes data take in Redshift?▼
Data arrives in Redshift as structured relational datasets that mirror your Ploomes object structure, with proper data typing for fields like amounts, dates, and status codes. Each pipeline becomes a separate dataset that you can query directly with SQL or connect to business intelligence tools like Power BI or Looker Studio.
Can I combine Ploomes data with other sources in Redshift?▼
Yes, once your Ploomes data resides in Redshift, you can join it with information from other Kondado sources such as BigQuery, PostgreSQL, or marketing platforms to create unified analytics datasets. This enables comprehensive reporting that correlates CRM activities with financial, operational, or marketing metrics.
Do I need coding skills to send Ploomes data to Redshift?▼
No coding is required to establish the connection or maintain data flows, as Kondado provides a no-code interface for selecting pipelines and configuring schedules. However, you will need SQL knowledge to query the replicated data in Redshift and build custom reports for your business needs.
Which Ploomes pipelines include sales and deal information?▼
The Deals pipeline contains order numbers, amounts, and stage progression data, while the Sales pipeline provides transaction details including customer IDs and total amounts. You can also replicate the Deal Stages and Sales Stages pipelines to analyze funnel progression and conversion metrics in your Redshift environment.
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