Are you using Segment to track event data and are looking to move this to a cloud data warehouse like Amazon Redshift for deeper, more meaningful analysis? You have landed on the right post.
This blog covers two methods to move data from Segment to Redshift. One approach would describe the native integration that Segment has with Redshift and the limitations that this method brings in. The second approach would involve an automated data pipeline platform like Hevo that can overcome the limitations of the first approach. Read on to understand both the approaches, weigh the pros and cons and finally choose the method that suits you best.
Introduction to Segment
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Segment is a Customer Data Platform that allows businesses to orchestrate events data from a wide range of source systems into different destinations. The most common use case where Segment is implemented is to track customer activity data such as product purchase, button clicks, and so on and then orchestrated into different marketing and sales platforms to achieve business outcomes. Segment receives, translates, and then sends data from any platform to more than 120 marketing and analytics applications.
A few key features of Segment are as follows:
- Provides access to all customer data that is tracked by your organization from a single API.
- Simplifies data integration tasks by minimizing the setup procedure.
- Allows you to enrich your collected customer data by providing connections to other tools. This helps you further enhance your decision-making process.
Introduction to Redshift
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Redshift is a columnar data warehouse managed by Amazon Web Services (AWS). It is designed to run complex analytical problems in a cost-efficient manner. It can store petabyte-scale data and enable fast analysis. Redshift’s completely managed warehouse setup, combined with its powerful MPP (massively parallel processing) has made it one of the most famous cloud data warehouse options among modern businesses. You can read more about the features of Redshift here.
Here are a few salient features of Redshift:
- Redshift ML: Redshift ML simplifies creating, training, and deploying Amazon SageMaker models using SQL for database developers and Data Analysts.
- Federated Query: The federated query allows you to reach into your operational, relational database. You can now query live data across one or more Aurora PostgreSQL and Amazon RDS databases to get instant visibility into the end-to-end business operations without the need for data movement.
- Materialized Views: This Redshift feature allows you to achieve faster query performance on datasets ranging in size from gigabytes to petabytes. Data Compression, Columnar Storage, and Zone Maps considerably reduce the amount of I/O needed to perform queries.
- Limitless Concurrency: Amazon Redshift provides fast performance consistently, even with thousands of concurrent queries, whether they query data directly in your Amazon S3 Data Lake, or in your Amazon Redshift Data Warehouse.
This blog covers two methods for migrating data from Segment to Redshift:
Method 1: Using Native Migration to Move Data from Segment to Redshift
Using Segments’ in-built Redshift connector, data can be transferred from Segment to Redshift easily. Segment allows connecting to Redshift and transferring data by streaming live events. This method requires setting up the Redshift data warehouse beforehand and keep it running during the process.
Method 2: Using Hevo Data to Move Data from Segment to Redshift
A fully managed, No-code Data Pipeline platform like Hevo Data, helps you load data from Segment (among numerous free data sources) to Redshift in real-time, in an effortless manner. Hevo with its minimal learning curve can be set up in a matter of minutes making the users ready to load data without compromising performance.
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Its strong integration with various sources such as databases, files, analytics engines, etc gives users the flexibility to bring in data of all different kinds in a way that’s as smooth as possible, without having to write a single line of code.
Understanding the Methods to Connect Segment to Redshift
There are multiple methods that can be used to connect Segment to Redshift and load data easily:
Method 1: Using Native Migration to Move Data from Segment to Redshift
Redshift Data Warehouse is one of the many destinations that Segment can send data to. You can directly connect to Redshift from within Segment and stream event data. Here are the steps:
Note, before attempting the following steps, make sure you have a Redshift data warehouse up and running.
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- In the Segment App, select ‘Add Destination.’
- Search and select ‘Redshift.’
- Select the sources you want to sync to this Warehouse.
- Enter your Redshift credentials
All the future events captured by Segment will now be loaded to Redshift.
Limitations of using Native Migration to Connect Segment to Redshift
While the above approach to move data is fairly simple, it does have a few limitations listed as follows:
- Data Sync Constraints: Segment limits the number of times the data can be synced to Redshift depending on the subscription plan you may have. In their free plan, you are allowed to load data once a day, and their team plan allows you to load data twice a day. The enterprise plan allows a near real-time data sync, but it can burn your pockets.
- Transformation of Data: If you want to transform the data before moving data to Redshift, Segment provides very basic features for this. If your use case demands a lot more complex data transformations, you would need to figure alternative ways to achieve this.
- Loading of Historical Data: Since you are looking to move data from Segment to Redshift, a good chance is that you already have the events data stored in a database. Segment can only bring “live”/future event data from your applications to Redshift. you will need to figure out an alternative way to move historical data to Redshift separately.
Method 2: Using Hevo Data to Move Data from Segment to Redshift
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Hevo Data, a No-code Data Pipeline can help you move data from Segment (among numerous free data sources) swiftly to Redshift. Hevo is fully managed and it completely automates the process of monitoring and replicating the changes on the secondary database rather than making the user write the code repeatedly. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss. Hevo allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiff.
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Steps to use Hevo Data:
Hevo Data focuses on two simple steps to get you started:
Configure Source: Authenticate and connect Segment to Hevo Data through Webhooks. To add the generated Webhook URL to your Segment account, just copy the URL and add it to your Segment account as a destination.
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Integrate Data: Load data from Segment to Redshift by providing your Redshift databases credentials like Database Port, Username, Password, Name, Schema, and Cluster Identifier along with the Destination Name.
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Advantages of using Hevo Data Platform:
- Real-Time Data Export: Hevo with its strong integration with 100+ sources, allows you to transfer data quickly & efficiently. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.
Conclusion
This blog talks about the two methods you can use to set up a connection from Segment to Redshift: using custom ETL scripts and with the help of a third-party tool, Hevo. It also gives a brief overview of Segment and Redshift highlighting their key features and benefits before diving into the setup process.
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Extracting complex data from a diverse set of data sources can be a challenging task and this is where Hevo saves the day! Hevo offers a faster way to move data from Databases or SaaS applications such as Segment into your Data Warehouse like Redshift to be visualized in a BI tool. Hevo is fully automated and hence does not require you to code.
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What are your thoughts on moving data from Segment to Redshift? Let us know in the comments.
Ameet is a seasoned freelance writer with a forte in the data industry who loves creating engaging content on topics like data analytics, machine learning, AI, big data, and business intelligence. His writing bridges technical complexities, offering diverse audiences informative insights and industry updates.
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