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When dealing with large data sets, it is not feasible to manage data transfers without tools that can efficiently scale. Heroku provides effective data management resources for managing data sets in your cloud data warehouse, but you still need tools that can make the ETL process simpler and as automated as possible. Here are the top five ETL tools for Heroku.

Key Features to Look For

To find the best ETL tools for data integration, it is important to know what to look for. Some features make tools nice to work with, but you need to focus on the features that make them necessary for your big data and business intelligence workflow. 

The tools that provide the most necessary features, like rest APIs, will give you the biggest impact on your time. Here are some of the features that you need in ETL tools.

Automation

Automation is essential when it comes to data management processes. The ability to run real-time data warehouse processes without the need for manual input makes an ETL tool powerful. Without that ability, you’ll find yourself spending a lot of time running basic MySQL processes rather than focusing on the higher-level things that you need to address. 

Types of Automation

There are different levels of automation to think about for ELT. In its most basic form, you need to be able to run scripts to process large segments of data. Working with databases means that you need to master data replication and manipulation. Scripts make that possible by running code that does the process that you need to extract data for data analytics dashboards, such as with Google Analytics.

Data management often requires running the same process repeatedly to find and manipulate data, whether in Java, Apache, AWS, or Amazon Redshift. Scripts automate these processes to a level of performance that humans cannot match. What would take you minutes to do, a computer with the right script can replicate thousands of times in a second. This is one of the most powerful features that a tool can have, and is arguably necessary for handling data on a business level. 

The other type of automation to think about is smart transactions. Smart transactions use AI (artificial intelligence) and ML (machine learning) to know when to use specific processes. A tool that can handle smart transactions can take a more active role in manipulating and analyzing enterprise data. 

AI systems can recognize specific conditions and respond by running the right script, whether on Python or Oracle. For example, the right tool can tell when the conditions are right to run an analysis of data for key performance indicators. These tools are very powerful and can drastically change how well your company processes data. 

1. Postgres

Postgres is a fast, mature open-source database management system (DBMS), with a large feature set. The Postgres command-line tools are simple to install and easy to use. Connections are pooled; therefore, the application can handle many concurrent connections without affecting performance. 

For these reasons, Postgres is ideal for data aggregation on Heroku. In Heroku, you will likely be using PostgreSQL to manage data, which leverages the abilities of SQL relational databases and Postgres for more powerful data modeling.

Postgres Is Open-Source 

One of the things that makes Postgres a great choice is that it is developed as an open-source project. This means that the application is available for free and there are many great contributors to the project. The open-source community consists of more than 3,000 contributors, with over one million lines of code written, all of which are available for free. 

What this means in terms of support is that Postgres has one of the strongest support communities and widespread adoption, as well as purpose-built plugins. It is a safe bet to base your workflows on Postgres since it is well supported and widely used. 

Heroku Postgres Scales on Demand

Another feature that makes Postgres a great choice is that it scales with your needs. Every company experiences fluctuations in its data processing needs. Sometimes, you need more processing power, storage, and bandwidth quickly to accommodate traffic increases. 

Heroku Postgres scales easily to meet the rise in resource demands. What could otherwise be a serious bottleneck for your company is something that Heroku Postgres is set up to handle.

2. Heroku Connect

Heroku Connect is a data synchronization service that runs on Heroku. Its primary purpose is to connect your Postgres databases with Salesforce CRM. Salesforce on its own is a powerful tool, but most sales organizations require large amounts of data to function. Connecting Salesforce with Postgres makes it possible for a sales organization to gather and manage all of the data in a CRM and perform data engineering processes to better understand markets and customers. 

No Coding Required

Because of the nature of the system, it is easy to see why people think that setting up Heroku Connect may be difficult. Creating bridges between programs seems like it would be a highly technical process, but there is no coding required thanks to creative systems like a drag-and-drop interface. 

Heroku keeps data warehousing and making connections simple and you do not need in-depth technical knowledge to make the system work for you. All you have to do is follow the setup instructions and you are ready to go with your own data sources fed into data pipelines.

3. Integrate.io

Integrate.io is a system that can help you automate much of your ETL process and data flows while improving compliance with regulations. Industries with strict data management regulations can benefit from a tool like Integrate.io. 

Pre-Built Data Transformations

One of the hardest parts of using the data that you have is creating data transformations with an API. Finding ways of transforming data to visualize it and make it useful, such as graphic visualizations, is built into Integrate.io. 

Integrate.io is a powerful tool because it lets you build your own transformations and already has a long list of transformations included. You can start creating data visualizations in powerful and useful ways using well-managed data flows without having to code transformations first. 

4. Heroku Redis

Although databases are very powerful tools, there are cases where companies need something else. Heroku Redis works with NoSQL database structures that are becoming increasingly popular. Structures like MongoDB work perfectly with Redis. 

Command Line Development

One of the things that makes Heroku Redis a powerful tool is its restructured command-line interface. In programming, the command line is one of the easiest and least-limited environments to develop in. Redis adds to this to make it easier to create apps only using the command line. You don’t need a complex interface or system, just access to the command line. This can serve as the connector.

5. Heroku Shield

Heroku Shield is a powerful ETL app that lets you build apps that are standards-compliant. Many industries have extensive regulations for data management and security that need to be addressed. With Heroku Shield, you can focus more on development with resources to make apps compliant to different standards. 

Integrated Security Features 

The reason why Heroku Shield makes apps more compliant is that it is built to use standards-compliant methods of assembling apps with templates. It has customized security systems in place that lend themselves to HIPAA and PCI compliance for data security and data quality. You are, essentially, starting from a place that is already focused on compliance rather than having to go back and check later. Before starting the process of data migration for data analysis purposes, select a solution with an easy-to-use user interface and security schema. 

Integrate.io Can Help You Choose ETL Tools

Every ETL tool is different, which is why you should lean on someone that can help you find the right tools. Integrate.io can help you find the right ETL tools, as well as help you find ways to better manage ETL and data management. Sign up for our seven-day trial to see how we can help you build a better data management infrastructure on Google Cloud, IBM cloud platform, or Microsoft Azure. Our team can give you more information about use cases, a tutorial, or pricing.